From ff172cd2ba17607918589f18a33d5228dfaf9be4 Mon Sep 17 00:00:00 2001 From: sowm9802 Date: Wed, 20 Nov 2024 21:01:56 +0530 Subject: [PATCH 1/3] OSPC-721: update openstack-glance-images.md with windows --- docs/openstack-glance-images.md | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/docs/openstack-glance-images.md b/docs/openstack-glance-images.md index db120371..15ae5ac4 100644 --- a/docs/openstack-glance-images.md +++ b/docs/openstack-glance-images.md @@ -390,3 +390,26 @@ openstack --os-cloud default image create \ --property os_version=9.4 \ RHEL-9.4 ``` + +## Get Windows + +!!! note + + You will need to create a virtual disk image from your own licensed media and convert to .qcow2 format. This example uses a Windows 2022 Standard Edition installation generalized with cloud-init and sysprep, then converted the image to .qcow2 format using qemu-img. For additional information on creating a Windows image, please see the [upstream documentation](https://docs.openstack.org/image-guide/create-images-manually-example-windows-image.html). + +``` shell +openstack --os-cloud default image create \ + --progress \ + --disk-format qcow2 \ + --min-disk 50 \ + --min-ram 2048 \ + --container-format bare \ + --file Windows2022StdEd.qcow2 \ + --public \ + --property hypervisor_type=kvm \ + --property os_type=windows \ + --property os_admin_user=administrator \ + --property os_distro=windows \ + --property os_version=2022 \ + Windows-2022-Standard +``` From 1b5d4393f66a7617c122be866b4521dec4300688 Mon Sep 17 00:00:00 2001 From: sowm9802 Date: Fri, 22 Nov 2024 18:56:41 +0530 Subject: [PATCH 2/3] OSPC-749: Flavor specific network bandwidth limits --- docs/openstack-flavors.md | 129 ++++++++++++++++++++++++-------------- 1 file changed, 81 insertions(+), 48 deletions(-) diff --git a/docs/openstack-flavors.md b/docs/openstack-flavors.md index 266a2be9..f39d2a6a 100644 --- a/docs/openstack-flavors.md +++ b/docs/openstack-flavors.md @@ -38,31 +38,31 @@ The Memory slot is an integrate representing the gigabytes of RAM a flavor will The flavors used within our Genestack environment have been built to provide the best possible default user experience. Our flavors create an environment with the following specifications. -| Name | GB | vCPU | Local Disk (GB) | Ephemeral Disk (GB) | Swap Space (MB) | -| ---- | -- | ---- | --------------- | ------------------- | --------------- | -| gp.0.1.2 | 2 | 1 | 10 | 0 | 0 | -| gp.0.1.4 | 4 | 1 | 10 | 0 | 0 | -| gp.0.2.2 | 2 | 2 | 40 | 0 | 1024 | -| gp.0.2.4 | 4 | 2 | 40 | 0 | 1024 | -| gp.0.2.6 | 6 | 2 | 40 | 0 | 1024 | -| gp.0.2.8 | 8 | 2 | 40 | 0 | 1024 | -| gp.0.4.4 | 4 | 4 | 80 | 64 | 4096 | -| gp.0.4.8 | 8 | 4 | 80 | 64 | 4096 | -| gp.0.4.12 | 12 | 4 | 80 | 64 | 4096 | -| gp.0.4.16 | 16 | 4 | 80 | 64 | 4096 | -| gp.0.8.16 | 16 | 8 | 160 | 128 | 8192 | -| gp.0.8.24 | 24 | 8 | 160 | 128 | 8192 | -| gp.0.8.32 | 32 | 8 | 160 | 128 | 8192 | -| gp.0.16.64 | 64 | 16 | 240 | 128 | 8192 | -| gp.0.24.96 | 96 | 24 | 240 | 128 | 8192 | -| gp.0.32.128 | 128 | 32 | 240 | 128 | 8192 | -| gp.0.48.192 | 192 | 48 | 240 | 128 | 8192 | -| mo.1.2.12 | 12 | 2 | 80 | 0 | 0 | -| mo.1.2.16 | 16 | 2 | 80 | 0 | 0 | -| mo.1.4.20 | 20 | 4 | 80 | 0 | 0 | -| mo.1.4.24 | 24 | 4 | 80 | 0 | 0 | -| mo.1.4.32 | 32 | 4 | 80 | 0 | 0 | -| mo.1.8.64 | 64 | 8 | 80 | 0 | 0 | +| Name | GB | vCPU | Local Disk (GB) | Ephemeral Disk (GB) | Swap Space (MB) | Max Network Bandwidth (Gbps) | +| ---- | -- | ---- | --------------- | ------------------- | --------------- | ---------------------------- | +| gp.0.1.2 | 2 | 1 | 10 | 0 | 0 | 2 | +| gp.0.1.4 | 4 | 1 | 10 | 0 | 0 | 4 | +| gp.0.2.2 | 2 | 2 | 40 | 0 | 1024 | 2 | +| gp.0.2.4 | 4 | 2 | 40 | 0 | 1024 | 4 | +| gp.0.2.6 | 6 | 2 | 40 | 0 | 1024 | 4 | +| gp.0.2.8 | 8 | 2 | 40 | 0 | 1024 | 6 | +| gp.0.4.4 | 4 | 4 | 80 | 64 | 4096 | 4 | +| gp.0.4.8 | 8 | 4 | 80 | 64 | 4096 | 6 | +| gp.0.4.12 | 12 | 4 | 80 | 64 | 4096 | 6 | +| gp.0.4.16 | 16 | 4 | 80 | 64 | 4096 | 8 | +| gp.0.8.16 | 16 | 8 | 160 | 128 | 8192 | 8 | +| gp.0.8.24 | 24 | 8 | 160 | 128 | 8192 | 10 | +| gp.0.8.32 | 32 | 8 | 160 | 128 | 8192 | 10 | +| gp.0.16.64 | 64 | 16 | 240 | 128 | 8192 | 10 | +| gp.0.24.96 | 96 | 24 | 240 | 128 | 8192 | 10 | +| gp.0.32.128 | 128 | 32 | 240 | 128 | 8192 | 10 | +| gp.0.48.192 | 192 | 48 | 240 | 128 | 8192 | 10 | +| mo.1.2.12 | 12 | 2 | 80 | 0 | 0 | 6 | +| mo.1.2.16 | 16 | 2 | 80 | 0 | 0 | 8 | +| mo.1.4.20 | 20 | 4 | 80 | 0 | 0 | 10 | +| mo.1.4.24 | 24 | 4 | 80 | 0 | 0 | 10 | +| mo.1.4.32 | 32 | 4 | 80 | 0 | 0 | 10 | +| mo.1.8.64 | 64 | 8 | 80 | 0 | 0 | 10 | ## Flavor Properties @@ -75,35 +75,42 @@ Flavor properties provide some additional configuration to highlight placement a | hw:cpu_max_sockets | 2 | Sets the max number of sockets used within the instances. While any integer is acceptible, the highest recommended maximum is 4. | | :category | String | Display property used within skyline to group flavor classes. Our options are `general_purpose`, `memory_optimized`, and `compute_optimized`. | | :architecture | x86_architecture | Display property used within skyline to group flavor classes. Our option is currently limited to `x86_architecture` | +| quota:vif_inbound_peak | int | Defines the maximum allowed inbound (ingress) bandwidth on the network interface, representing the peak throughput for incoming data to the instance. The speed limit values are specified in kilobytes/second | +| quota:vif_inbound_burst | int | Specifies the maximum burst rate for inbound traffic. The burst is the allowance for temporary spikes in traffic, higher than the average rate but still within the maximum peak limit. The burst value is in kilobytes | +| quota:vif_inbound_average | int | Sets the average allowable bandwidth for inbound traffic over a sustained period. This is typically the sustained rate at which the instance can receive data, usually lower than the peak and burst rates. The speed limit values are specified in kilobytes/second | +| quota:vif_outbound_peak | int | Defines the maximum bandwidth allowed for outbound (egress) traffic on the network interface. Similar to inbound, it sets the peak limit for data leaving the instance. The speed limit values are specified in kilobytes/second | +| quota:vif_outbound_burst | int | Specifies the maximum burst rate for outbound traffic, allowing short-term spikes in the outgoing traffic, similar to the inbound burst rate. The burst value is in kilobytes | +| quota:vif_outbound_average | int | Sets the average bandwidth for outbound traffic over time, ensuring that the sustained outgoing traffic rate does not exceed this value over a longer period. The speed limit values are specified in kilobytes/second | + ---- ??? example "Example Creation of Flavors Built for Production" ``` shell - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 2048 --vcpu 1 --disk 10 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.1.2 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 1 --disk 10 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.1.4 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 2048 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.2.2 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.2.4 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 6144 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.2.6 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 8192 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.2.8 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.4.4 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 8192 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.4.8 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 12288 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.4.12 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.4.16 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.8.16 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 24576 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.8.24 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 32768 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.8.32 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 65536 --vcpu 16 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.16.64 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 98304 --vcpu 24 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.24.96 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 131072 --vcpu 32 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.32.128 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 196608 --vcpu 48 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" gp.0.48.192 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 12288 --vcpu 2 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.2.12 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 2 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.2.16 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 20480 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.4.20 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 24576 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.4.24 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 32768 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.4.32 - openstack --os-cloud default flavor create --description "Useful Information for users" --ram 65536 --vcpu 8 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" mo.0.8.64 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 2048 --vcpu 1 --disk 10 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="250000" --property "quota:vif_inbound_burst"="250000" --property "quota:vif_inbound_average"="125000" --property "quota:vif_outbound_peak"="250000" --property "quota:vif_outbound_burst"="250000" --property "quota:vif_outbound_average"="125000" gp.0.1.2 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 1 --disk 10 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="500000" --property "quota:vif_inbound_burst"="500000" --property "quota:vif_inbound_average"="250000" --property "quota:vif_outbound_peak"="500000" --property "quota:vif_outbound_burst"="500000" --property "quota:vif_outbound_average"="250000" gp.0.1.4 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 2048 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="250000" --property "quota:vif_inbound_burst"="250000" --property "quota:vif_inbound_average"="125000" --property "quota:vif_outbound_peak"="250000" --property "quota:vif_outbound_burst"="250000" --property "quota:vif_outbound_average"="125000" gp.0.2.2 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="500000" --property "quota:vif_inbound_burst"="500000" --property "quota:vif_inbound_average"="250000" --property "quota:vif_outbound_peak"="500000" --property "quota:vif_outbound_burst"="500000" --property "quota:vif_outbound_average"="250000" gp.0.2.4 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 6144 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="500000" --property "quota:vif_inbound_burst"="500000" --property "quota:vif_inbound_average"="312500" --property "quota:vif_outbound_peak"="500000" --property "quota:vif_outbound_burst"="500000" --property "quota:vif_outbound_average"="312500" gp.0.2.6 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 8192 --vcpu 2 --disk 40 --ephemeral 0 --swap 1024 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="750000" --property "quota:vif_inbound_burst"="750000" --property "quota:vif_inbound_average"="375000" --property "quota:vif_outbound_peak"="750000" --property "quota:vif_outbound_burst"="750000" --property "quota:vif_outbound_average"="375000" gp.0.2.8 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 4096 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="500000" --property "quota:vif_inbound_burst"="500000" --property "quota:vif_inbound_average"="250000" --property "quota:vif_outbound_peak"="500000" --property "quota:vif_outbound_burst"="500000" --property "quota:vif_outbound_average"="250000" gp.0.4.4 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 8192 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="750000" --property "quota:vif_inbound_burst"="750000" --property "quota:vif_inbound_average"="375000" --property "quota:vif_outbound_peak"="750000" --property "quota:vif_outbound_burst"="750000" --property "quota:vif_outbound_average"="375000" gp.0.4.8 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 12288 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="750000" --property "quota:vif_inbound_burst"="750000" --property "quota:vif_inbound_average"="437500" --property "quota:vif_outbound_peak"="750000" --property "quota:vif_outbound_burst"="750000" --property "quota:vif_outbound_average"="437500" gp.0.4.12 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 4 --disk 80 --ephemeral 64 --swap 4096 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1000000" --property "quota:vif_inbound_burst"="1000000" --property "quota:vif_inbound_average"="500000" --property "quota:vif_outbound_peak"="1000000" --property "quota:vif_outbound_burst"="1000000" --property "quota:vif_outbound_average"="500000" gp.0.4.16 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1000000" --property "quota:vif_inbound_burst"="1000000" --property "quota:vif_inbound_average"="500000" --property "quota:vif_outbound_peak"="1000000" --property "quota:vif_outbound_burst"="1000000" --property "quota:vif_outbound_average"="500000" gp.0.8.16 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 24576 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="687500" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="687500" gp.0.8.24 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 32768 --vcpu 8 --disk 160 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="750000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="750000" gp.0.8.32 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 65536 --vcpu 16 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="875000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="875000" gp.0.16.64 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 98304 --vcpu 24 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="937500" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="937500" gp.0.24.96 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 131072 --vcpu 32 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="1000000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="1000000" gp.0.32.128 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 196608 --vcpu 48 --disk 240 --ephemeral 128 --swap 8192 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=general_purpose" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="1062500" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="1062500" gp.0.48.192 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 12288 --vcpu 2 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="750000" --property "quota:vif_inbound_burst"="750000" --property "quota:vif_inbound_average"="437500" --property "quota:vif_outbound_peak"="750000" --property "quota:vif_outbound_burst"="750000" --property "quota:vif_outbound_average"="437500" mo.0.2.12 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 16384 --vcpu 2 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1000000" --property "quota:vif_inbound_burst"="1000000" --property "quota:vif_inbound_average"="500000" --property "quota:vif_outbound_peak"="1000000" --property "quota:vif_outbound_burst"="1000000" --property "quota:vif_outbound_average"="500000" mo.0.2.16 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 20480 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="625000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="625000" mo.0.4.20 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 24576 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="687500" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="687500" mo.0.4.24 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 32768 --vcpu 4 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="750000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="750000" mo.0.4.32 + openstack --os-cloud default flavor create --description "Useful Information for users" --ram 65536 --vcpu 8 --disk 80 --ephemeral 0 --swap 0 --property "hw:mem_page_size=any" --property "hw:cpu_max_threads=1" --property "hw:cpu_max_sockets=2" --property ":category=memory_optimized" --property ":architecture=x86_architecture" --property "quota:vif_inbound_peak"="1250000" --property "quota:vif_inbound_burst"="1250000" --property "quota:vif_inbound_average"="875000" --property "quota:vif_outbound_peak"="1250000" --property "quota:vif_outbound_burst"="1250000" --property "quota:vif_outbound_average"="875000" mo.0.8.64 ``` ## Use Case Specific Flavors @@ -131,6 +138,32 @@ openstack --os-cloud default flavor set intel.medium \ --property capabilities:cpu_info:vendor='Intel' ``` +### Example: Network Bandwidth Limits + +This example configures a flavor to use network traffic bandwidth limits for outbound and inbound traffic + +``` shell +openstack --os-cloud default flavor create gp.0.8.24 \ + --public \ + --ram 24576 \ + --disk 160 \ + --vcpus 8 \ + --ephemeral 128 \ + --swap 8192 +``` + +Now, set the following properties: `vif_inbound_average`, `vif_inbound_burst`, `vif_inbound_peak`, `vif_outbound_average`, `vif_outbound_burst`, and `vif_outbound_peak`. These values define the respective limits for network traffic. The speed limits are specified in kilobytes per second (kB/s), while the burst values are also specified in kilobytes. + +```shell +openstack --os-cloud default flavor set gp.0.8.24 \ + --property "quota:vif_inbound_peak"="1250000" \ + --property "quota:vif_inbound_burst"="1250000" \ + --property "quota:vif_inbound_average"="687500" \ + --property "quota:vif_outbound_peak"="1250000" \ + --property "quota:vif_outbound_burst"="1250000" \ + --property "quota:vif_outbound_average"="687500" +``` + ### Example: NUMA Preferred Affinity Policy This example configures a flavor to use the preferred PCI NUMA affinity policy for any Neutron SR-IOV interfaces. From b24bc28ff2ddcb7f8dc4bbe47219819639dc9762 Mon Sep 17 00:00:00 2001 From: sowm9802 Date: Tue, 26 Nov 2024 11:14:22 +0530 Subject: [PATCH 3/3] Changes from PR 579 and fixed syntax and workflow issues --- ...g-infrastructure-CiscoN9K-C93108TC-FX3P.md | 123 ++++++++ ...puting-infrastructure-CiscoN9K-C93180YC.md | 147 +++++++++ ...ng-infrastructure-CiscoWS-C2960X-48TD-L.md | 133 ++++++++ ...ted-computing-infrastructure-DL380-Gen9.md | 141 +++++++++ ...ated-computing-infrastructure-DellR7515.md | 77 +++++ ...ated-computing-infrastructure-DellR7615.md | 91 ++++++ ...ated-computing-infrastructure-DellR7625.md | 91 ++++++ ...ted-computing-infrastructure-DellXE7100.md | 101 ++++++ ...ted-computing-infrastructure-DellXE8640.md | 104 +++++++ ...erated-computing-infrastructure-F5i5800.md | 107 +++++++ ...lerated-computing-infrastructure-PA5420.md | 117 +++++++ docs/accelerated-computing-infrastructure.md | 29 ++ docs/accelerated-computing-overview.md | 294 ++++++++++++++++++ mkdocs.yml | 3 + 14 files changed, 1558 insertions(+) create mode 100644 docs/accelerated-computing-infrastructure-CiscoN9K-C93108TC-FX3P.md create mode 100644 docs/accelerated-computing-infrastructure-CiscoN9K-C93180YC.md create mode 100644 docs/accelerated-computing-infrastructure-CiscoWS-C2960X-48TD-L.md create mode 100644 docs/accelerated-computing-infrastructure-DL380-Gen9.md create mode 100644 docs/accelerated-computing-infrastructure-DellR7515.md create mode 100644 docs/accelerated-computing-infrastructure-DellR7615.md create mode 100644 docs/accelerated-computing-infrastructure-DellR7625.md create mode 100644 docs/accelerated-computing-infrastructure-DellXE7100.md create mode 100644 docs/accelerated-computing-infrastructure-DellXE8640.md create mode 100644 docs/accelerated-computing-infrastructure-F5i5800.md create mode 100644 docs/accelerated-computing-infrastructure-PA5420.md create mode 100644 docs/accelerated-computing-infrastructure.md create mode 100644 docs/accelerated-computing-overview.md diff --git a/docs/accelerated-computing-infrastructure-CiscoN9K-C93108TC-FX3P.md b/docs/accelerated-computing-infrastructure-CiscoN9K-C93108TC-FX3P.md new file mode 100644 index 00000000..3e3167c4 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-CiscoN9K-C93108TC-FX3P.md @@ -0,0 +1,123 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Cisco Nexus N9K-C93108TC-FX3P + +The Cisco Nexus N9K-C93108TC-FX3P is a high-performance, fixed-port switch in the Cisco Nexus 9000 Series. +It is designed for data centers and enterprise networks requiring high-speed connectivity, flexible +port configurations, advanced programmability, and support for modern applications like software-defined +networking (SDN) and intent-based networking. Below are the key features of the Cisco Nexus N9K-C93108TC-FX3P: + + 1. **High Port Density and Versatile Connectivity**: The N9K-C93108TC-FX3P provides 48 10GBASE-T ports + that support speeds of 100 Mbps, 1 Gbps, 10 Gbps, and in some cases, even 25 Gbps. This flexibility + makes it suitable for connecting various devices within a data center or enterprise network. + 6 x 40/100-Gigabit Ethernet QSFP28 Uplinks: It includes 6 uplink ports that support 40G and 100G + speeds, enabling high-speed connections to spine switches or core layers for optimal data center + scalability and performance. + + 2. **High Performance and Throughput**: Up to 3.6 Tbps of Switching Capacity: With up to 3.6 Tbps throughput + and up to 1.4 Bpps of forwarding performance, the switch can handle substantial traffic loads, + which is essential for high-performance environments. Low Latency: The switch is designed with + low-latency architecture, making it suitable for latency-sensitive applications such as financial + trading, storage networking, and high-performance computing. + + 3. **Advanced Layer 2 and Layer 3 Features**: The switch provides comprehensive Layer 2 and Layer 3 switching + and routing features, including support for VLANs, VXLAN, Routing Information Protocol (RIP), Open + Shortest Path First (OSPF), Border Gateway Protocol (BGP), and Enhanced Interior Gateway Routing + Protocol (EIGRP). VXLAN and EVPN: With Virtual Extensible LAN (VXLAN) and Ethernet VPN (EVPN) + capabilities, the switch allows for scalable multi-tenant network segmentation, enabling organizations + to create isolated virtual networks across Layer 3 domains. Advanced Multicast Capabilities: It + includes support for Protocol Independent Multicast (PIM), Internet Group Management Protocol (IGMP), + and Multicast Listener Discovery (MLD) for efficient handling of multicast traffic. + + 4. **Programmability and Automation**: The N9K-C93108TC-FX3P can operate in Cisco NX-OS mode for traditional + environments or in Cisco Application Centric Infrastructure (ACI) mode for SDN and policy-driven + networking, providing flexibility in deployment. The switch supports RESTful APIs, Python scripting, + and Linux-based programmability, allowing network operators to automate and streamline network + management tasks. Real-time telemetry provides deep visibility into network traffic and device health, + enabling proactive monitoring and troubleshooting. This feature can be integrated with Cisco Nexus + Dashboard Insights or third-party analytics tools. + + 5. **Power over Ethernet (PoE) and PoE+ Support**: The N9K-C93108TC-FX3P supports up to 60W of Power over + Ethernet (PoE) on 36 ports, providing enough power for devices such as IP phones, wireless access + points, and IoT devices. The switch complies with the IEEE 802.3bt standard, allowing it to provide + PoE++ capabilities, which are essential for high-power devices. + + 6. **Security and Policy Management**: MACsec provides encryption on wired connections, ensuring data + security on critical network links and protecting against unauthorized interception. Access Control + Lists (ACLs) and Role-Based Access Control (RBAC): The switch includes granular ACLs and RBAC for + controlling access to network resources and restricting user actions based on roles, enhancing + overall security. The switch provides Control Plane Policing (CoPP) and Dynamic ARP Inspection + (DAI), which protect it from malicious attacks and prevent disruptions to network traffic. + + 7. **Energy Efficiency and High Availability**: The switch includes front-to-back or back-to-front airflow + options, along with redundant power supply support, enabling it to fit into a variety of data center + cooling configurations. It also has hot-swappable fans and power supplies for minimal service + interruption. Cisco EnergyWise: EnergyWise technology optimizes energy consumption, reducing the + overall energy footprint and operational costs. + + 8. **Quality of Service (QoS) and Application Prioritization**: The switch includes features like Weighted + Random Early Detection (WRED) and priority flow control, allowing administrators to prioritize + critical application traffic, ensure smooth performance for latency-sensitive applications, and + reduce congestion. The switch supports eight egress queues per port, enabling granular traffic + management for different classes of service, which helps ensure consistent performance for high-priority + applications. + + 9. **Spine-Leaf Architecture Compatibility**: The N9K-C93108TC-FX3P is well-suited for deployment as a + leaf switch in a leaf-spine architecture, enabling easy scalability and predictable performance. + It allows organizations to scale their network in a modular fashion by adding more leaf switches + as required, without requiring changes in the spine layer. + + 10. **Support for Cisco Intelligent Traffic Director (ITD)**: Cisco Intelligent Traffic Director (ITD) + provides efficient traffic distribution across multiple servers, reducing the need for a dedicated + load balancer and maximizing server utilization. ITD is particularly useful in clustered application + environments, such as data analytics or web hosting, where traffic needs to be evenly distributed + across multiple servers. + + 11. **Flexible Management Options**: The switch offers multiple management interfaces, including the + traditional CLI, a web-based UI, and support for APIs, giving network teams flexibility in their + preferred management approach. Integration with Cisco DNA Center and Nexus Dashboard enables + centralized policy management, monitoring, and orchestration, simplifying operations and improving + network visibility. + + 12. **IPv6 Support and Network Compatibility**: The N9K-C93108TC-FX3P includes comprehensive support for + IPv6, which is crucial for organizations preparing for future network growth and ensuring compatibility with next-generation internet protocols. + +In summary, the Cisco Nexus N9K-C93108TC-FX3P is a versatile, high-performance switch ideal for data centers and high-speed enterprise networks. With multispeed 1/10/25-GbE access ports, 40/100-GbE uplinks, PoE++ capabilities, comprehensive Layer 2 and Layer 3 support, and programmability, it provides the scalability, security, and flexibility needed in modern network environments. It supports both Cisco ACI for SDN and traditional NX-OS, allowing it to be used in both traditional and software-defined networks. These features make it suitable for organizations looking for a high-speed, secure, and energy-efficient solution that supports evolving data center needs. + +### **Ideal Use Cases** + +* **High-Density Data Center Access Layer**: Data centers that need flexible port speeds to connect a range + of devices, including virtualized servers, storage systems, and applications requiring high throughput. + +* **Leaf Switch in Spine-Leaf Architecture**: Organizations needing a scalable, high-performance data center + that can grow easily by adding more leaf switches to accommodate new servers or applications. + +* **Software-Defined Networking (SDN) and Cisco ACI Deployments**: Enterprises or data centers aiming to + simplify network management, increase automation, and improve agility by using policy-driven + configurations. + +* **Edge Computing and IoT Deployments with PoE Needs**: Organizations deploying IoT devices, large-scale + Wi-Fi, or industrial environments where power and network connectivity need to be converged at the + edge. + +* **Secure Segmentation and Multitenant Environments**: Hosting providers, cloud service providers, or any + enterprise that requires secure segmentation to support multiple departments or customer environments + on a shared infrastructure. + +* **Virtualized and Hybrid Cloud Workloads**: Enterprises adopting hybrid cloud models or using heavy virtualization, + as it provides the necessary performance, connectivity, and management features for smooth operations. + +* **Data-Intensive and Latency-Sensitive Applications**: Financial services, healthcare, and research institutions + that rely on real-time data processing and high-performance computing. + +* **Centralized Management and Automation-Driven Networks**: Enterprises with complex network infrastructures + that aim to reduce manual tasks and improve efficiency through automated configuration, monitoring, + and troubleshooting. + +* **Enhanced Security Environments**: Financial institutions, government agencies, or any organization needing + robust security measures to protect sensitive data or comply with regulatory requirements. + +* **Load Balancing and Traffic Distribution for High Availability**: Web hosting, e-commerce, and content + delivery networks that need to manage traffic efficiently and provide high availability for applications. diff --git a/docs/accelerated-computing-infrastructure-CiscoN9K-C93180YC.md b/docs/accelerated-computing-infrastructure-CiscoN9K-C93180YC.md new file mode 100644 index 00000000..8823a792 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-CiscoN9K-C93180YC.md @@ -0,0 +1,147 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Cisco Nexus N9K-C93180YC-FX + +The Cisco Nexus N9K-C93180YC-FX (also known as the Nexus 93180YC-FX) is a high-performance, fixed-port +switch designed for modern data centers and enterprise networks that need high-speed, low-latency connectivity. +It’s part of Cisco’s Nexus 9000 series and is optimized for next-generation networking environments, +including those that use software-defined networking (SDN) and intent-based networking. Here are the +key features of the Cisco Nexus N9K-C93180YC-FX: + + 1. **High-Speed 1/10/25/40/100 Gigabit Ethernet Ports**: The N9K-C93180YC-FX is a 1RU switch that provides + 48 1/10/25-Gigabit Ethernet (GbE) ports and 6 40/100-GbE ports. It supports flexible configurations, + with each 25-GbE port also able to operate at 10 Gbps, and the 40/100-GbE ports can be used for + uplinks to connect to higher-speed switches or spine layers. This flexibility makes it suitable + for a variety of network topologies, whether leaf-spine in data centers or as a high-speed aggregation + switch in enterprise networks. + + 2. **High-Performance and Low-Latency Architecture**: The N9K-C93180YC-FX delivers up to 3.6 Tbps of throughput + and 1.2 Bpps of packet forwarding capacity, supporting environments with large amounts of data + and low-latency requirements. It’s built on a high-performance ASIC that provides consistent low + latency, making it ideal for latency-sensitive applications like high-frequency trading, storage + networking, and real-time analytics. + + 3. **Programmability and Automation with NX-OS and ACI Mode**: The switch can operate in Cisco NX-OS mode + for traditional network environments or in Application Centric Infrastructure (ACI) mode for SDN + environments. In NX-OS mode, it provides advanced programmability with support for Python scripting, + REST APIs, and other automation tools, making it easy to integrate into modern DevOps workflows. + In ACI mode, it can be part of Cisco’s ACI framework, enabling centralized, policy-driven network + management and simplifying the management of complex network architectures. + + 4. **VXLAN Support for Network Virtualization**: The N9K-C93180YC-FX provides VXLAN (Virtual Extensible LAN) + support, allowing it to extend Layer 2 networks over Layer 3 infrastructure. VXLAN is essential + for building scalable multi-tenant cloud environments, enabling virtualized networks, and supporting + flexible network segmentation. It allows organizations to deploy virtual networks across multiple + data centers, making it ideal for cloud environments and software-defined data centers. + + 5. **Advanced Telemetry and Analytics**: Cisco has built advanced telemetry features into the N9K-C93180YC-FX, + which can provide real-time insights into network traffic and health without impacting performance. + It supports Streaming Telemetry, which sends detailed network data to monitoring platforms, helping + administrators identify potential issues and optimize network performance proactively. The telemetry + features can be used with Cisco’s Nexus Dashboard Insights or third-party analytics tools to gain + deep visibility into the network. + + 6. **Comprehensive Security Features**: The switch supports a range of security features, including MACsec + (802.1AE), which provides data encryption on the wire for secure link-level communication. It also + includes features like role-based access control (RBAC), Control Plane Policing (CoPP), and Dynamic + ARP Inspection (DAI), which enhance the security and stability of the network. Security Group Access + Control Lists (SGACLs) and IP Access Control Lists (IP ACLs) are also available to enforce granular + security policies and protect the network from unauthorized access. + + 7. **Scalability with Large MAC and Route Table Sizes**: The N9K-C93180YC-FX has a large MAC address table + and forwarding table, supporting up to 256,000 entries, making it ideal for large-scale environments + with many connected devices. It supports IPv4 and IPv6 routing capabilities, enabling it to handle + complex network topologies and a large number of routes, which is beneficial in both enterprise + and cloud data centers. + + 8. **Flexible Buffering and Quality of Service (QoS)**: This switch includes dynamic buffer allocation, + which allows for efficient packet queuing and prevents congestion during traffic spikes, especially + useful for high-throughput applications. The advanced Quality of Service (QoS) features prioritize + critical traffic, allowing administrators to allocate bandwidth based on application requirements, + ensuring consistent performance for priority applications. + + 9. **Cisco Intelligent Traffic Director (ITD)**: ITD is a load-balancing feature available on the N9K-C93180YC-FX + that enables efficient traffic distribution across multiple servers without requiring a dedicated + load balancer. It can support load balancing based on server utilization, maximizing resource efficiency + and improving application availability. This feature is especially useful in scenarios where traffic + needs to be distributed across a cluster of servers, such as in large-scale data analytics or web + applications. + + 10. **Integration with Cisco Tetration and Nexus Dashboard**: The N9K-C93180YC-FX is compatible with Cisco + Tetration, which provides deep visibility, analytics, and security for data centers by monitoring + and analyzing every packet in real-time. It also integrates with Cisco Nexus Dashboard, allowing + for centralized management of Nexus switches and providing insights into application performance + and network operations. These integrations help organizations gain comprehensive control over + network security, compliance, and overall performance. + + 11. **Flexible Cooling and Power Options**: The switch supports front-to-back or back-to-front airflow, + allowing for deployment in various data center cooling configurations. The redundant, hot-swappable + power supplies and fans ensure continuous operation and minimize downtime in case of hardware + failure. + + 12. **Layer 2 and Layer 3 Multicast Support**: The N9K-C93180YC-FX includes extensive support for Layer 2 + and Layer 3 multicast, allowing for efficient distribution of data across multiple hosts, which + is valuable in applications like media streaming and real-time data sharing. It supports protocols + like PIM (Protocol Independent Multicast), IGMP (Internet Group Management Protocol), and MLD + (Multicast Listener Discovery) to provide robust multicast capabilities. + + 13. **Easy Scalability in Leaf-Spine Architecture**: The N9K-C93180YC-FX is well-suited for leaf-spine + architectures, which provide scalable and predictable performance by minimizing the number of + hops between devices. It’s an ideal choice for organizations looking to deploy modular and scalable + network topologies in modern data centers, with support for rapid expansion as data center demands + grow. + + 14. **Energy Efficient and Compact Design**: Built with energy efficiency in mind, the N9K-C93180YC-FX + uses lower power consumption, making it a sustainable choice for data centers aiming to reduce + their energy footprint. Its compact 1RU form factor also allows it to fit into high-density deployments, + optimizing data center space while delivering substantial networking power. + +In summary, the Cisco Nexus N9K-C93180YC-FX is a versatile and high-performance switch designed for +modern data center environments, with a range of features optimized for scalability, flexibility, and +security. With its high port density, support for multi-speed ports, advanced programmability, VXLAN +support, and robust security capabilities, it is ideal for environments with intensive traffic management, +cloud deployments, and SDN-based architectures. Its flexibility in operating modes, extensive telemetry, +and support for automation tools make it a suitable choice for organizations seeking high-performance +networking with advanced control and monitoring capabilities. + +### **Ideal Use Cases** + +* **High-Density Data Center Access Layer**: Data centers requiring flexible, high-speed access to support + server and storage connections at a variety of speeds, from legacy 1G to modern 10G, 25G, and 100G. + +* **Leaf Switch in Spine-Leaf Architectures**: Organizations building scalable data centers with spine-leaf + architectures, especially those that expect to grow rapidly and need the flexibility to expand by + adding more leaf switches. + +* **Software-Defined Networking (SDN) and Cisco ACI Environments**: Enterprises that want the ability to + automate network configuration and management with ACI or use hybrid SDN to simplify network operations, + reduce downtime, and improve agility. + +* **Multi-Tenant and Virtualized Environments**: Cloud service providers and enterprises managing virtualized + environments, where isolation between tenant networks is crucial and scalability is a requirement. + +* **Storage Area Networks (SAN) and Hyperconverged Infrastructure (HCI)**: Enterprises with high-performance + storage needs, such as those deploying HCI solutions (e.g., Cisco HyperFlex, Nutanix) or using Ethernet-based + SANs, including iSCSI and Fibre Channel over Ethernet (FCoE). + +* **Application Environments Requiring Low Latency and High Throughput**: Financial services, research institutions, + and data centers with high-performance computing needs, such as scientific simulations and machine + learning workloads. + +* **Automated and Programmable Networks**: Enterprises and service providers looking to reduce manual tasks, + improve network efficiency, and implement Infrastructure-as-Code (IaC) with centralized management. + +* **Centralized Monitoring and Analytics-Driven Operations**: Enterprises seeking improved network visibility, + faster troubleshooting, and proactive management in data center environments where uptime and performance + are critical. + +* **Security-Focused Deployments**: Organizations in regulated industries, like finance and healthcare, + where network security and data protection are high priorities. + +* **Hybrid Cloud and Multi-Cloud Interconnectivity**: Enterprises adopting hybrid or multi-cloud strategies + and requiring seamless integration and secure connectivity between private and public cloud environments. + +* **Quality of Service (QoS) for Business-Critical Applications**: Data centers supporting diverse application + workloads, including video conferencing, VoIP, and latency-sensitive applications like trading platforms. diff --git a/docs/accelerated-computing-infrastructure-CiscoWS-C2960X-48TD-L.md b/docs/accelerated-computing-infrastructure-CiscoWS-C2960X-48TD-L.md new file mode 100644 index 00000000..367304c8 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-CiscoWS-C2960X-48TD-L.md @@ -0,0 +1,133 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Cisco Catalyst WS-C2960X-48TD-L + +The Cisco Catalyst WS-C2960X-48TD-L is a member of Cisco’s Catalyst 2960-X series switches, which are +popular in enterprise campus and branch network deployments. The WS-C2960X-48TD-L model is designed to +provide robust and reliable Layer 2 and basic Layer 3 network services, with high availability, security, +and energy efficiency features. Here are the key features of the Cisco Catalyst WS-C2960X-48TD-L: + + 1. **High Port Density with Gigabit Ethernet Access Ports**: This model offers 48 Gigabit Ethernet ports, + which provide 10/100/1000 Mbps connectivity for endpoint devices such as computers, printers, + IP phones, and wireless access points. The high port density is ideal for connecting a large number + of devices in a single switch, making it well-suited for access-layer deployments in enterprise + networks. + + 2. **10 Gigabit Ethernet Uplinks**: The WS-C2960X-48TD-L includes 2 SFP+ ports that support 10 Gigabit + Ethernet uplinks, allowing for high-speed connectivity to the distribution layer or core network. + These 10 GbE uplinks provide significant bandwidth, enabling faster data transmission and supporting + applications that require high throughput. + + 3. **Layer 2 Switching with Basic Layer 3 Capabilities**: Primarily a Layer 2 switch, the WS-C2960X-48TD-L + supports VLANs, trunking, and Spanning Tree Protocol, which enables segmentation and traffic management + at the access layer. It includes basic Layer 3 features, such as static routing and limited RIP + (Routing Information Protocol) support, which can be used for simple IP routing within a local + network. These Layer 3 features allow for inter-VLAN routing, making it possible to route traffic + between different VLANs without needing a dedicated router for basic routing tasks. + + 4. **Energy Efficiency with Cisco EnergyWise**: The Catalyst WS-C2960X-48TD-L switch supports Cisco EnergyWise + technology, which allows administrators to monitor and manage the power consumption of connected + devices. EnergyWise reduces power consumption during off-peak hours and can adjust power settings + based on usage patterns, contributing to reduced energy costs and a more sustainable network. + + 5. **Stacking with FlexStack-Plus**: The switch is compatible with Cisco FlexStack-Plus, which allows + up to 8 switches to be stacked and managed as a single unit. Stacking enhances scalability and + simplifies management by consolidating multiple switches into a single control plane, making it + easy to add capacity to the network as needed. FlexStack-Plus provides up to 80 Gbps of stacking + bandwidth, enabling resilient and high-speed connections between stacked switches, which supports + high availability. + + 6. **Enhanced Security Features**: The WS-C2960X-48TD-L includes several built-in security features, + such as 802.1X authentication for network access control, port security to limit MAC addresses + on each port, and DHCP snooping to protect against rogue DHCP servers. Access Control Lists (ACLs) + provide granular control over traffic to prevent unauthorized access to sensitive areas of the + network. The switch also supports IP Source Guard and Dynamic ARP Inspection (DAI) to protect against + IP spoofing and ARP attacks, enhancing network security. + + 7. **High Availability with Redundant Power Options**: While the switch does not have hot-swappable power + supplies, it supports external redundant power supplies (RPS 2300) for improved reliability and + high availability. Redundant power is essential for critical applications, as it ensures the switch + remains operational even in the event of a primary power failure. + + 8. **Advanced Quality of Service (QoS)**: The WS-C2960X-48TD-L includes QoS features that allow administrators + to prioritize critical traffic, such as voice and video, ensuring a consistent user experience + for latency-sensitive applications. With 4 egress queues per port and features like Weighted Round + Robin (WRR) scheduling, administrators can control bandwidth allocation and optimize network performance + for priority applications. + + 9. **Cisco IOS Software with a User-Friendly Interface**: Running Cisco IOS LAN Base software, the switch + provides an intuitive user interface and reliable performance for managing network services. The + LAN Base software is tailored for Layer 2 switching and includes essential features for campus + network deployments, including VLAN management, Spanning Tree Protocol, and multicast support. + Cisco’s web-based management interface and CLI (command-line interface) make configuration and + troubleshooting straightforward, which simplifies management and maintenance. + + 10. **Cisco Catalyst Smart Operations for Simplified Management**: Cisco Catalyst Smart Operations features, + such as Auto Smartports and Smart Install, help automate configurations and simplify switch deployment. + Auto Smartports automatically configures settings on switch ports based on the connected device + type, which reduces setup time and minimizes errors. Smart Install allows for zero-touch deployment + of new switches, ideal for remote branch offices or large campus environments that require consistent + configuration across devices. + + 11. **Enhanced Network Resilience**: The switch includes Spanning Tree Protocol (STP) support, including + features like Per-VLAN Spanning Tree (PVST) and Rapid Spanning Tree Protocol (RSTP), which enhance + network redundancy and prevent loops. The EtherChannel feature aggregates multiple physical links + into a single logical link for greater bandwidth and link redundancy, which is essential for + maintaining network uptime. + + 12. **Support for IPv6**: The WS-C2960X-48TD-L provides native support for IPv6, ensuring compatibility + with modern network environments and future-proofing the network for growth and expansion. + + 13. **Energy Efficient Ethernet (EEE) Support**: The switch includes Energy Efficient Ethernet (EEE) + support, which reduces power consumption during periods of low network activity. This feature + enables the switch to save energy without affecting performance, contributing to a lower overall + power footprint for the network infrastructure. + +In summary, the Cisco Catalyst WS-C2960X-48TD-L is a reliable, energy-efficient Layer 2 switch with +basic Layer 3 routing capabilities, designed for high-density access deployments in campus and branch +networks. With 48 Gigabit Ethernet ports and two 10-Gigabit uplinks, it provides ample connectivity for +endpoint devices and uplink capacity to connect to higher layers in the network. Its stacking capabilities, +security features, QoS, and energy management make it suitable for environments that require stable, +high-availability access layer networking with simplified management and operational efficiency. + +### **Ideal Use Cases** + +* **High-Density Data Center Access Layer**: Data centers requiring flexible, high-speed access to support + server and storage connections at a variety of speeds, from legacy 1G to modern 10G, 25G, and 100G. + +* **Leaf Switch in Spine-Leaf Architectures**: Organizations building scalable data centers with spine-leaf + architectures, especially those that expect to grow rapidly and need the flexibility to expand by + adding more leaf switches. + +* **Software-Defined Networking (SDN) and Cisco ACI Environments**: Enterprises that want the ability to + automate network configuration and management with ACI or use hybrid SDN to simplify network operations, + reduce downtime, and improve agility. + +* **Multi-Tenant and Virtualized Environments**: Cloud service providers and enterprises managing virtualized + environments, where isolation between tenant networks is crucial and scalability is a requirement. + +* **Storage Area Networks (SAN) and Hyperconverged Infrastructure (HCI)**: Enterprises with high-performance + storage needs, such as those deploying HCI solutions (e.g., Cisco HyperFlex, Nutanix) or using Ethernet-based + SANs, including iSCSI and Fibre Channel over Ethernet (FCoE). + +* **Application Environments Requiring Low Latency and High Throughput**: Financial services, research + institutions, and data centers with high-performance computing needs, such as scientific simulations + and machine learning workloads. + +* **Automated and Programmable Networks**: Enterprises and service providers looking to reduce manual tasks, + improve network efficiency, and implement Infrastructure-as-Code (IaC) with centralized management. + +* **Centralized Monitoring and Analytics-Driven Operations**: Enterprises seeking improved network visibility, + faster troubleshooting, and proactive management in data center environments where uptime and performance + are critical. + +* **Security-Focused Deployments**: Organizations in regulated industries, like finance and healthcare, + where network security and data protection are high priorities. + +* **Hybrid Cloud and Multi-Cloud Interconnectivity**: Enterprises adopting hybrid or multi-cloud strategies + and requiring seamless integration and secure connectivity between private and public cloud environments. + +* **Quality of Service (QoS) for Business-Critical Applications**: Data centers supporting diverse application + workloads, including video conferencing, VoIP, and latency-sensitive applications like trading platforms. diff --git a/docs/accelerated-computing-infrastructure-DL380-Gen9.md b/docs/accelerated-computing-infrastructure-DL380-Gen9.md new file mode 100644 index 00000000..24e5517b --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DL380-Gen9.md @@ -0,0 +1,141 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## HPE ProLiant DL380 Gen9 + +The HPE ProLiant DL380 Gen9 is a versatile and reliable server designed to handle a wide variety of +workloads in data centers, ranging from traditional business applications to virtualized environments +and data-intensive tasks. Here are the key features of the DL380 Gen9: + + 1. **Scalability and Performance**: + * **Dual-Socket Support**: The DL380 Gen9 supports two Intel Xeon E5-2600 v3 or v4 series processors, + offering up to 44 cores per server (22 cores per processor) for significant multi-threaded performance. + + * **High Memory Capacity**: With 24 DIMM slots, the server supports up to 3 TB of DDR4 RAM (when using + 128 GB LRDIMMs), providing ample memory for memory-intensive applications and virtualized environments. + + * **Enhanced Compute Power**: The Intel Xeon E5-2600 v3/v4 processors provide improved power efficiency + and processing power, making the DL380 Gen9 suitable for modern enterprise workloads. + + 2. Flexible Storage Options: + * **Up to 24 SFF (Small Form Factor) Drives or 12 LFF (Large Form Factor) Drives**: The DL380 Gen9 can + accommodate a variety of storage configurations, including a mix of SAS, SATA, and NVMe drives. + This flexibility allows for a mix of high-performance storage (e.g., SSDs) and high-capacity + storage (e.g., HDDs). + + * **Support for NVMe SSDs**: NVMe support enables faster storage performance, which is crucial for + workloads that require high-speed I/O, such as database applications and analytics. + + * **HPE Smart Array Controllers**: Integrated with HPE’s Smart Array controllers, the DL380 Gen9 offers + advanced storage management, data protection, and RAID functionality for improved performance and + data redundancy. + + 3. High Availability and Redundancy: + * **Redundant Power Supplies**: The DL380 Gen9 supports hot-swappable, redundant power supplies, which + provide continuous operation in the event of a power supply failure, enhancing uptime. + + * **Hot-Plug Fans and Drives**: It includes hot-pluggable fans and drive bays, allowing for hardware + maintenance without downtime, which is essential for mission-critical applications. + + * **RAID Support**: The HPE Smart Array controllers provide RAID support to enhance data redundancy + and improve fault tolerance, with options for RAID 0, 1, 5, 6, 10, 50, and 60. + + 4. **Networking and Expansion Capabilities**: + * **Embedded 4 x 1GbE Ports**: The DL380 Gen9 comes with four embedded 1 GbE ports, providing network + connectivity for standard workloads. + + * **FlexibleLOM (FlexibleLAN on Motherboard)**: The FlexibleLOM slot allows users to customize their + networking configuration, including options for 10 GbE and 25 GbE network adapters. + + * **Multiple PCIe Slots**: With up to 6 PCIe 3.0 slots, the server allows for significant expansion, + including support for additional NICs, HBAs, and GPUs, giving flexibility for future upgrades + and integration with storage and network infrastructure. + + 5. **GPU Support for Acceleration**: The DL380 Gen9 supports GPU accelerators for compute-intensive applications, + including NVIDIA GPUs, making it suitable for machine learning, AI, and high-performance computing + (HPC) workloads. This capability enables the DL380 Gen9 to handle workloads that require massive + parallel processing, such as scientific simulations, engineering modeling, and deep learning. + + 6. **Advanced Management with HPE iLO 4**: HPE Integrated Lights-Out (iLO 4) provides comprehensive remote + management and monitoring, allowing administrators to manage and troubleshoot the server remotely. + Intelligent Provisioning and Active Health System: Built-in tools like Intelligent Provisioning + simplify server deployment, while the Active Health System continuously monitors the server’s health + and logs system events for proactive management. Remote Console and Virtual Media: iLO offers a + graphical remote console and virtual media support, which streamlines maintenance and reduces the + need for physical access. + + 7. Advanced Security Features: + * **Secure Boot and Firmware Validation**: The DL380 Gen9 includes secure boot and runtime firmware + validation to protect against firmware-level attacks. + + * **TPM (Trusted Platform Module) Support**: The DL380 Gen9 supports TPM 1.2 and 2.0, providing enhanced + hardware-based security for encryption and key storage. + + * **Lockable Drive Bays**: Physical security is enhanced with lockable drive bays, reducing the risk + of unauthorized physical access to the storage drives. + + 8. Energy Efficiency: + * **HPE Power Supplies with 80 PLUS Platinum and Titanium Efficiency**: These high-efficiency power + supplies help reduce power consumption and overall energy costs, which is essential for data + centers aiming to minimize their carbon footprint. + + * **HPE Power Regulator and Dynamic Power Capping**: HPE’s power management tools allow the DL380 Gen9 + to optimize power usage dynamically, saving energy based on workload requirements. + + 9. **Operating System and Hypervisor Support**: The DL380 Gen9 is compatible with a wide range of operating + systems, including Microsoft Windows Server, Red Hat Enterprise Linux, SUSE Linux Enterprise Server, + Ubuntu, VMware ESXi, and others. This broad compatibility makes it a suitable choice for diverse + environments, supporting both physical and virtualized deployments with ease. + + 10. **Modular Design for Flexibility**: + * **Tool-Free Access**: The DL380 Gen9 has a tool-free design, allowing for easy upgrades and maintenance, + which reduces downtime and operational complexity. + + * **Optional Optical Drive Bay**: The server provides an option for an optical drive bay, which can + be useful for software installations and backups in environments that still rely on physical media. + +In summary, the HPE ProLiant DL380 Gen9 is a powerful, versatile, and energy-efficient server well-suited +for a range of enterprise applications, from general-purpose tasks to demanding workloads like virtualization, +database management, and compute-heavy analytics. With support for dual CPUs, high memory capacity, +flexible storage options, and GPU acceleration, it provides the performance and scalability required +for modern data center needs. Its advanced management, security, and power efficiency features make it +an excellent choice for organizations seeking a balance of performance, reliability, and operational simplicity. + +### **Ideal Use Cases** + +* **Virtualization and Cloud Infrastructure**: Organizations looking to reduce physical server sprawl, increase + resource utilization, and improve flexibility in workload management. + +* **Database and Analytics Workloads**: Enterprises that need reliable, high-performance database servers + for online transaction processing (OLTP), data warehousing, or big data analytics. + +* **High-Performance Computing (HPC) and Scientific Applications**: Research institutions, universities, + and engineering firms needing a scalable platform to perform computationally demanding tasks. + +* **Application Hosting and Web Services**: Small to large enterprises that require a stable and powerful + platform for hosting diverse business applications and web services. + +* **Backup and Disaster Recovery Solutions**: Organizations looking for a dependable backup solution or + a disaster recovery server to protect critical data and ensure business continuity. + +* **Software-Defined Storage (SDS)**: Enterprises looking to implement a flexible, scalable storage solution + without investing in dedicated storage hardware. + +* **Hyperconverged Infrastructure (HCI)**: Businesses that want a unified infrastructure solution to simplify + management, reduce costs, and improve scalability. + +* **Edge Computing and Remote Office Deployments**: Enterprises needing processing capabilities at remote + sites or branch offices without compromising on performance and reliability. + +* **Enterprise File and Print Services**: Organizations needing centralized, high-availability file storage + and print management. + +* **Development and Testing Environments**: Development teams that need dedicated resources for software + testing, application development, and quality assurance activities. + +* **Security Applications (Firewall, IDS/IPS)**: Enterprises implementing network security solutions in-house, + especially in regulated industries or organizations with stringent security requirements. + +* **Email and Collaboration Platforms**: Organizations that host on-premises email and collaboration systems + for security, compliance, or operational preferences. diff --git a/docs/accelerated-computing-infrastructure-DellR7515.md b/docs/accelerated-computing-infrastructure-DellR7515.md new file mode 100644 index 00000000..442dc363 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DellR7515.md @@ -0,0 +1,77 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Dell PowerEdge R7515 + +The Dell PowerEdge R7515 is a high-performance, single-socket server optimized for handling demanding +workloads in data centers and edge environments. Its combination of powerful AMD EPYC processors, large +memory capacity, and storage flexibility makes it particularly suited for virtualization, software-defined +storage, and data analytics. Here are the key features of the Dell PowerEdge R7515: + + 1. **Processor Performance**: The R7515 is powered by a single AMD EPYC processor, which can have up to + 64 cores per processor, allowing it to handle multi-threaded workloads efficiently. AMD EPYC processors + are known for high core counts, large cache sizes, and fast memory bandwidth, making the R7515 an + excellent choice for applications requiring parallel processing power, such as virtualization and + data analytics. + + 2. **Memory Capacity and Speed**: The server supports up to 2TB of DDR4 RAM across 16 DIMM slots, allowing + for significant memory capacity, which is ideal for memory-intensive applications. With support for + memory speeds of up to 3200 MT/s, the R7515 can handle large datasets and in-memory databases effectively, + providing faster access to frequently accessed data. + + 3. **Storage Flexibility**: The R7515 offers flexible storage options, supporting up to 24x 2.5" drives or + 12x 3.5" drives, including options for NVMe, SAS, and SATA drives. NVMe support allows for ultra-fast + storage performance, which is ideal for workloads that require low-latency data access, like high-frequency + trading or large-scale databases. It also supports M.2 SSDs for fast boot drives, optimizing system + startup and application load times. + + 4. **High-Speed Networking Options**: The R7515 offers multiple networking options, including support + for up to four embedded 10GbE ports, as well as additional networking through PCIe expansion slots. + This flexibility enables high-speed data transfer, suitable for network-intensive applications. + It supports Smart NICs and other accelerators, which are valuable in environments where network + performance and offloading network tasks are essential. + + 5. **I/O and Expansion**: The R7515 provides up to 6 PCIe 4.0 expansion slots, allowing for fast connectivity + with additional hardware such as GPUs, FPGAs, and other accelerators, enabling it to handle AI, + machine learning, and other specialized computing tasks. PCIe 4.0 doubles the data throughput compared + to PCIe 3.0, allowing faster data transfer rates for connected components. + + 6. **Advanced Cooling and Power Efficiency**: The R7515 includes multi-vector cooling technology that + adjusts airflow based on system demands, which helps maintain performance while minimizing power + consumption. Dell’s power management and cooling options make the R7515 energy-efficient, allowing + for reduced operational costs in data centers and edge deployments. + + 7. **Security Features**: R7515 includes Dell’s Cyber Resilient Architecture, which incorporates features + such as secure boot, system lockdown, and hardware root of trust, helping protect data from unauthorized + access and tampering. The iDRAC9 (Integrated Dell Remote Access Controller) offers secure, remote + management and monitoring capabilities, as well as alerting and automation features to detect and + respond to security threats. + + 8. **Management and Automation Tools**: Dell OpenManage and iDRAC9 provide powerful management capabilities, + allowing administrators to remotely monitor, manage, and update the server. Features like the iDRAC + RESTful API with Redfish, OpenManage Mobile, and SupportAssist streamline server management and + improve the efficiency of IT teams. Lifecycle Controller simplifies deployment and updates, allowing + administrators to manage firmware and configurations from a centralized console. + + 9. **Virtualization and Cloud-Ready Features**: The R7515 is designed with virtualization and software-defined + storage in mind, making it well-suited for virtualized environments, such as VMware and Microsoft + Hyper-V. It supports Dell’s VxRail and VMware’s vSAN Ready Nodes, allowing it to be integrated easily + into hyper-converged infrastructure (HCI) and software-defined environments. + + 10. **AI and Machine Learning Inference**: Expansion slots and GPU support allow the R7515 to handle inference + tasks, making it suitable for edge AI applications and other machine learning workloads. Software-Defined + Storage (SDS): The high-density storage capabilities are ideal for SDS environments, offering cost-effective + and scalable storage solutions. + +In summary, the Dell PowerEdge R7515 is a versatile, high-performance server with ample processing power, +flexible storage, and extensive I/O options, making it a strong choice for data centers and enterprises +needing a single-socket solution for virtualization, data analytics, and edge computing. Its flexibility +and scalability make it adaptable to a wide range of workloads and industries. + +### **Ideal Use Cases** + +* **Virtualization**: With high core counts, ample memory capacity, and storage options, the R7515 is + well-suited for running multiple virtual machines and supporting virtual desktop infrastructure (VDI). +* **Data Analytics and Big Data**: Large storage capacity, memory scalability, and support for high-speed + I/O make it effective for data analytics and big data applications. diff --git a/docs/accelerated-computing-infrastructure-DellR7615.md b/docs/accelerated-computing-infrastructure-DellR7615.md new file mode 100644 index 00000000..10e2b8b6 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DellR7615.md @@ -0,0 +1,91 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Dell PowerEdge R7615 + +The Dell PowerEdge R7615 is a single-socket, 2U rack server optimized for performance, scalability, +and flexibility, particularly for data-intensive and compute-heavy workloads. Leveraging AMD EPYC processors, +the R7615 offers strong performance with a focus on high memory and storage capacity, making it suitable +for various applications, including virtualization, database management, and AI inference. Here are +the key features of the Dell PowerEdge R7615: + + 1. **High-Performance Single-Socket Architecture**: The R7615 supports a single AMD EPYC 9004 series processor, + which can have up to 96 cores, providing a balance of high processing power and efficiency. AMD EPYC + processors are known for high core counts, memory bandwidth, and excellent floating-point performance, + making the R7615 a powerful choice for applications that require a large number of threads and efficient + parallel processing. + + 2. **Extensive Memory Capacity and Bandwidth**: The server supports up to 6TB of DDR5 memory across 12 + DIMM slots, allowing it to handle memory-intensive applications effectively. DDR5 memory provides + faster speeds (up to 4800 MT/s) and improved power efficiency compared to DDR4, enabling the R7615 + to manage large data sets and support applications requiring high memory bandwidth, such as databases + and data analytics. + + 3. **Flexible and High-Speed Storage Options**: The R7615 offers a range of storage configurations, supporting + up to 24x 2.5" NVMe or SAS/SATA drives or 12x 3.5" drives, allowing for a flexible and scalable + storage setup. NVMe support provides ultra-fast storage performance and low latency, which is beneficial + for applications that demand rapid data access, such as transactional databases, virtual desktop + infrastructure (VDI), and high-frequency trading. It also supports M.2 boot drives for dedicated + operating system storage, improving reliability and boot speed. + + 4. **Advanced Networking Options**: The R7615 includes embedded networking options, such as up to 4 x 10GbE + ports, which provide high-speed data transfer capabilities. Support for Smart NICs (network interface + cards with offload capabilities) enables improved performance for network-heavy applications, as + these can offload certain tasks from the CPU. + + 5. **Enhanced I/O with PCIe Gen 5.0**: With up to 8 PCIe Gen 5.0 expansion slots, the R7615 offers extensive + I/O capabilities, allowing for fast connectivity with GPUs, FPGAs, and other accelerators. PCIe + Gen 5.0 doubles the data throughput compared to PCIe Gen 4.0, making it suitable for applications + requiring high-speed data transfer, such as AI inference, high-performance computing (HPC), and + real-time analytics. + + 6. **GPU and Accelerator Support for AI and ML**: The R7615 can be configured with multiple GPUs, including + support for up to 4 single-width GPUs or 2 double-width GPUs, enabling it to handle AI and machine + learning inference tasks. This support makes the R7615 an ideal choice for organizations looking + to implement AI inference at scale or edge AI applications, where low-latency processing is essential. + + 7. **Efficient Power and Cooling Management**: The R7615 features Dell’s multi-vector cooling technology, + which dynamically adjusts airflow based on the server’s needs. This improves efficiency by optimizing + cooling while reducing power consumption. Power supplies with up to 96% (Titanium) efficiency ensure + that the R7615 can maintain high performance while minimizing energy costs, which is critical in + high-density data center environments. + + 8. **Built-In Security Features**: The server incorporates Dell’s Cyber Resilient Architecture, which + includes secure boot, hardware root of trust, and firmware protection, helping to safeguard against + unauthorized access and cyber threats. iDRAC9 (Integrated Dell Remote Access Controller) provides + secure, remote management capabilities, including automated alerts and monitoring to detect potential threats. + + 9. **Robust Management and Automation Tools**: Dell’s OpenManage suite, along with iDRAC9, simplifies + server management by providing tools for monitoring, updating, and maintaining the server. The + iDRAC RESTful API with Redfish and OpenManage Integration for VMware vCenter allow for integration + with existing IT infrastructure, enabling easier management in large-scale deployments. + + 10. **Hyper-Converged and Virtualization-Ready**: The R7615 is optimized for hyper-converged infrastructure + (HCI) solutions, supporting platforms like VMware vSAN and Microsoft Azure Stack HCI. This makes + it a solid option for virtualization workloads, supporting applications such as VDI, software-defined + storage, and multi-tenant environments. + + 11. **Edge and Data Center Versatility**: With its high core count, large memory capacity, and extensive + storage options, the R7615 is versatile enough to support various deployments, from data centers + to edge computing environments. This versatility makes the server ideal for edge scenarios where + powerful computing, local storage, and low latency are essential. + +In summary, the Dell PowerEdge R7615 is a robust and versatile single-socket server that combines powerful +AMD EPYC processors, extensive memory, high-speed I/O, and flexible storage to support demanding workloads. +Its flexibility, scalability, and performance make it an ideal choice for a wide range of applications, +including AI, data analytics, virtualization, and edge computing deployments. + +### **Ideal Use Cases** + +* **Virtualization and Cloud Computing**: High memory capacity and processing power make the R7615 suitable + for virtualization platforms and cloud-native applications. + +* **Data Analytics and Big Data**: The high memory bandwidth, scalable storage options, and fast I/O capabilities + are ideal for data analytics and big data processing. + +* **AI and Machine Learning Inference**: With support for multiple GPUs, the R7615 can accelerate AI inference + tasks, making it suitable for edge AI applications where latency is critical. + +* **High-Performance Computing (HPC)**: Single-socket scalability, high memory capacity, and PCIe Gen 5.0 + support make the R7615 a viable option for HPC workloads that require substantial computational power. diff --git a/docs/accelerated-computing-infrastructure-DellR7625.md b/docs/accelerated-computing-infrastructure-DellR7625.md new file mode 100644 index 00000000..a0ddfa07 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DellR7625.md @@ -0,0 +1,91 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Dell PowerEdge R7625 + +The Dell PowerEdge R7625 is a dual-socket, 2U server that offers advanced performance, scalability, and +flexibility for data-intensive workloads, high-performance computing (HPC), and artificial intelligence (AI) +applications. Built on the AMD EPYC architecture, it is designed to handle demanding applications across +enterprise data centers and cloud environments. Here are the key features of the Dell PowerEdge R7625: + + 1. **High-Performance Dual-Socket Architecture**: The R7625 supports dual AMD EPYC 9004 series processors, + which can have up to 96 cores per processor, providing up to 192 cores per server. This architecture + is ideal for multi-threaded and compute-intensive applications. AMD EPYC processors offer high + memory bandwidth, large cache sizes, and strong floating-point performance, which are essential for + tasks like scientific computing, machine learning, and large-scale analytics. + + 2. **Massive Memory Capacity and Bandwidth**: With support for up to 12TB of DDR5 RAM across 24 DIMM slots, + the R7625 provides extensive memory capacity, which is critical for memory-intensive applications. + DDR5 memory offers higher data rates and improved power efficiency compared to DDR4, with speeds + up to 4800 MT/s, allowing the server to handle larger datasets with faster access times. + + 3. **Flexible and High-Speed Storage Options**: The R7625 supports a mix of NVMe, SAS, and SATA drives, + allowing for a flexible storage configuration tailored to workload requirements. It can support + up to 24x 2.5" NVMe or SAS/SATA drives or 12x 3.5" SAS/SATA drives. NVMe storage support enables + ultra-fast storage performance and low latency, making it ideal for data-intensive tasks such as + databases, analytics, and high-frequency trading. The server also supports up to 4 M.2 SSDs for + fast and reliable boot and caching. + + 4. **Advanced Networking Capabilities**: The R7625 offers several embedded networking options, including + up to 4 x 10GbE ports, with additional networking options through PCIe slots. It supports Smart NICs + and other networking accelerators, which are beneficial in network-heavy environments, as they offload + network processing from the CPU and improve overall system performance. + + 5. **Enhanced I/O with PCIe Gen 5.0**: The server features up to 12 PCIe 5.0 expansion slots, providing + significant bandwidth improvements (up to double the bandwidth of PCIe 4.0) for connected devices. + PCIe Gen 5.0 allows for faster connectivity with GPUs, FPGAs, and other accelerators, making the + R7625 suitable for AI, deep learning, and other data-intensive applications that benefit from high-speed I/O. + + 6. **GPU and Accelerator Support for AI and ML**: The R7625 can accommodate up to 6 single-width or 3 + double-width GPUs, supporting a range of AI and machine learning applications. GPU support includes + NVIDIA A100 and other high-performance models, enabling accelerated performance for deep learning, + image processing, and other compute-intensive tasks. This support is particularly beneficial in + environments where large neural network models are used, such as AI training and inference. + + 7. Efficient Cooling and Power Management: Dell’s multi-vector cooling technology dynamically adjusts + airflow and cooling based on system workload and temperature, allowing for optimized power usage. + The R7625 is designed with energy efficiency in mind, featuring titanium-grade power supplies and + intelligent cooling. These features help reduce power consumption and cooling costs, which is critical + in large-scale data centers. + + 8. **Built-In Security Features**: The R7625 incorporates Dell’s Cyber Resilient Architecture, including + secure boot, system lockdown, and a hardware root of trust. These features protect the server against + firmware attacks and unauthorized access. The iDRAC9 (Integrated Dell Remote Access Controller) + enables secure, remote server management, along with automated alerts and threat detection, enhancing + the security and resilience of the server. + + 9. Comprehensive Management and Automation Tools: Dell’s OpenManage suite and iDRAC9 provide powerful + tools for monitoring, managing, and automating server maintenance, helping reduce the burden on IT + teams. Support for iDRAC RESTful API with Redfish and OpenManage Integration for VMware vCenter + offers easy integration into existing IT infrastructures, improving efficiency in large deployments. + + 10. Hyper-Converged Infrastructure (HCI) Ready: The R7625 is ideal for HCI solutions, supporting both + VMware vSAN and Microsoft Azure Stack HCI, making it easy to deploy in virtualized and cloud environments. + Dell offers VxRail-ready configurations that allow for integration into hyper-converged environments, + making it suitable for workloads that require high scalability and resilience, such as databases, VDI, + and software-defined storage. + + 11. Edge and Data Center Versatility: With its powerful processing, memory capacity, and GPU support, + the R7625 is suitable for a wide range of environments, from core data centers to edge locations. + The server’s versatility makes it a solid choice for edge deployments where robust computing power + and reliable storage are needed without the space for larger server racks. + +In summary, the Dell PowerEdge R7625 is a powerful, flexible, and scalable dual-socket server suited for +high-performance, data-intensive applications. With dual AMD EPYC processors, massive memory and storage +capacity, GPU support, and advanced networking options, the R7625 is well-equipped for AI, HPC, cloud, +and data analytics workloads in both data centers and edge deployments. + +### **Ideal Use Cases** + +* **AI and Machine Learning**: The support for multiple GPUs and high-core processors make it ideal for training + and inference tasks. + +* **Data Analytics and Big Data**: High memory capacity, storage flexibility, and fast I/O are essential for + handling large datasets and complex queries in analytics workloads. + +* **Virtualization and Cloud**: The extensive memory and processing power make the R7625 a strong choice for + running multiple virtual machines and managing virtualized environments. + +* **Scientific and Technical Computing**: With its high core count, fast memory, and advanced I/O, the R7625 + is excellent for computationally intensive applications, including simulations, research, and data analysis. diff --git a/docs/accelerated-computing-infrastructure-DellXE7100.md b/docs/accelerated-computing-infrastructure-DellXE7100.md new file mode 100644 index 00000000..aeca106d --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DellXE7100.md @@ -0,0 +1,101 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Dell PowerEdge XE7100 + +The Dell PowerEdge XE7100 is a high-density, 5U server designed specifically for massive storage capacity +and optimized for data-intensive workloads. This server is ideal for cloud providers, content delivery +networks, and environments that require large-scale data storage, such as AI/ML, big data analytics, +and media streaming. The XE7100 is part of Dell's Extreme Scale Infrastructure (ESI) portfolio, designed +to offer customizable and scalable solutions for unique data storage and processing needs. Here are the +relevant features of the Dell PowerEdge XE7100: + + 1. **Massive Storage Density**: The XE7100 supports up to 100 drives, with configurations allowing for + either: + * 100 x 3.5” drives (SAS/SATA) for traditional high-capacity storage. + * 72 x 3.5” drives (SAS/SATA) combined with 32 x 2.5” NVMe drives, providing a mix of high-capacity + and high-performance storage options. + This storage capacity is ideal for high-density storage applications such as object storage, software-defined storage, and large-scale data lakes. + + 2. **Flexible Storage Tiering**: By supporting both SAS/SATA (3.5” HDDs) and NVMe (2.5” SSDs), the XE7100 + allows for flexible storage tiering. NVMe drives provide ultra-fast storage for applications that + require low latency and high IOPS, while SATA drives offer cost-effective capacity for bulk storage. + This flexibility makes the XE7100 suitable for mixed-workload environments, allowing organizations + to combine fast access with cost-effective capacity. + + 3. **Dual-Socket Architecture with AMD EPYC Processors**: The XE7100 is powered by dual AMD EPYC processors, + which can offer up to 128 cores combined (64 cores per processor), providing substantial processing + power for managing and processing large datasets. AMD EPYC processors provide high memory bandwidth + and support a large number of PCIe lanes, which enhances the server’s ability to handle data-intensive + tasks and parallel processing. + + 4. **High Memory Capacity and Bandwidth**: The server supports up to 4TB of DDR4 memory across 32 DIMM + slots, providing ample memory for caching, indexing, and in-memory processing, which is critical + for data-intensive workloads. Memory speeds up to 3200 MT/s enable faster data access and throughput, + enhancing performance for analytics and data processing applications. + + 5. **Optimized for High Data Throughput with PCIe Expansion**: The XE7100 includes multiple PCIe 4.0 slots, + allowing for high data transfer rates between storage, processors, and network interfaces. PCIe Gen + 4.0 provides double the data transfer rate of PCIe Gen 3.0, which is beneficial for applications with + heavy I/O requirements, such as real-time data analytics or media streaming. + + 6. **Flexible Networking Options**: The XE7100 can be configured with various networking options, including + support for multiple 10GbE or 25GbE connections, ensuring high-speed network connectivity to handle + large data transfers. It supports Smart NICs and additional networking interfaces through PCIe slots, + allowing offloading of certain network tasks from the CPU to improve overall system performance. + + 7. **Enhanced Cooling and Power Efficiency**: The XE7100 is engineered with high-efficiency power supplies + and advanced airflow design, optimizing cooling for high-density storage configurations and reducing + power consumption. Multi-vector cooling technology ensures that each drive bay and component receives + the necessary airflow, even with densely packed storage, making it highly efficient in energy use. + + 8. **Efficient and Scalable Management Tools**: Dell’s OpenManage suite, including iDRAC9, offers comprehensive + server management, monitoring, and maintenance tools, which are essential for managing the large + storage infrastructure in the XE7100. OpenManage Integration with VMware vCenter and Redfish API + support allow for seamless integration into existing IT infrastructures, streamlining operations + for large-scale data environments. + + 9. **Security Features for Data Protection**: The XE7100 includes Dell’s Cyber Resilient Architecture, + which incorporates features such as secure boot, system lockdown, and a hardware root of trust + to safeguard the system against cyber threats. It offers physical security features to prevent + unauthorized access to the drives and components, which is critical for protecting sensitive data + in storage-heavy deployments. + + 10. Customizable and Modular Design: The XE7100 is part of Dell’s Extreme Scale Infrastructure (ESI) + portfolio, which means it is customizable to meet the specific needs of different data-intensive + applications. Customers can configure the drive and networking options according to their workload + requirements. This modularity allows businesses to tailor the XE7100 to fit within diverse data + center architectures, whether for cloud storage, content delivery, or software-defined storage. + + 11. **Edge and Data Center Deployment Versatility**: The XE7100’s high storage density and data throughput + capabilities make it suitable for both core data center deployments and edge locations that require + significant local storage. With its massive storage capabilities, the XE7100 can reduce the need + for frequent data transfers to and from the cloud, which is beneficial for edge environments with + intermittent connectivity or bandwidth limitations. + +In summary, the Dell PowerEdge XE7100 is a high-density, single-socket server with massive storage capabilities, +designed for workloads that require vast storage and flexible tiering options. Its high core count, large +memory capacity, and flexible networking make it ideal for applications in big data, content delivery, +object storage, and analytics. As a part of Dell’s Extreme Scale Infrastructure (ESI) portfolio, the XE7100 +is customizable to meet various storage and performance needs in modern data-intensive environments. + +### **Ideal Use Cases** + +* **Object and Software-Defined Storage**: The high-density storage configuration makes the XE7100 ideal + for object storage applications and software-defined storage solutions that require both scalability + and high capacity. + +* **Content Delivery and Media Streaming**: With support for NVMe storage and high-speed networking, the + XE7100 is suited for content delivery networks (CDNs) and media streaming platforms where low latency + and high throughput are crucial. + +* **Big Data Analytics and AI**: The large storage capacity and high memory options allow it to manage big + data workloads effectively, enabling fast data retrieval for analytics and AI training tasks. + +* **Backup and Archival Solutions**: The server’s cost-effective high-capacity storage is suitable for backup + and archival purposes, providing massive storage that can retain historical data for long periods. + +* **HPC Storage Nodes**: With high storage density and powerful processing capabilities, the XE7100 can + be deployed as a storage node within high-performance computing (HPC) clusters, enabling faster access + to data sets in scientific and technical applications. diff --git a/docs/accelerated-computing-infrastructure-DellXE8640.md b/docs/accelerated-computing-infrastructure-DellXE8640.md new file mode 100644 index 00000000..48f048d9 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-DellXE8640.md @@ -0,0 +1,104 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Dell PowerEdge XE8640 + +The Dell PowerEdge XE8640 is a high-performance server designed specifically for intensive artificial +intelligence (AI) and machine learning (ML) workloads, high-performance computing (HPC), and data analytics +applications. As part of Dell’s Extreme Scale Infrastructure (ESI) portfolio, the XE8640 combines powerful +GPU capabilities with high-density compute power in a 2U form factor, making it ideal for environments +that require intensive processing and large-scale computational capabilities. Here are the key features +of the Dell PowerEdge XE8640: + + 1. **High-Density 2U Form Factor for GPU Acceleration**: The XE8640 is a 2U server that is optimized for + high-density GPU configurations, allowing for intensive compute capabilities in a compact design. + This form factor makes it ideal for data centers that need to maximize performance per rack unit + without sacrificing processing power. + + 2. **Support for High-Performance GPUs**: The XE8640 can be configured with up to 4 double-width GPUs, + including options for NVIDIA A100 Tensor Core GPUs or NVIDIA H100 GPUs for AI and ML acceleration. + These GPUs deliver significant computational power, with support for FP64, FP32, FP16, and INT8 + precision operations, enabling a wide range of AI/ML, data analytics, and HPC workloads. The use + of multiple GPUs provides enhanced parallel processing power, ideal for deep learning model training, inferencing, and data processing tasks. + + 3. **Dual-Socket AMD EPYC Processors**: The XE8640 is powered by dual AMD EPYC processors, offering up + to 128 cores combined (64 cores per processor). AMD EPYC CPUs are known for high memory bandwidth + and ample PCIe lanes, which optimize data flow between GPUs and CPUs and provide the necessary + resources for compute-intensive applications. This powerful CPU configuration enhances overall + performance for applications that require a mix of CPU and GPU processing. + + 4. **Large Memory Capacity and Bandwidth**: The server supports up to 4TB of DDR4 memory across 32 DIMM + slots, providing substantial memory resources for large datasets, model training, and in-memory + processing. With memory speeds up to 3200 MT/s, the XE8640 ensures efficient data transfer between + the memory and processors, which is critical for data-intensive applications. This high memory + capacity is particularly beneficial for AI and HPC applications where data throughput and low latency + are essential. + + 5. **Extensive PCIe 4.0 and NVMe Support**: The XE8640 includes support for PCIe Gen 4.0, providing double + the data transfer rate of PCIe Gen 3.0, which is essential for high-performance GPUs and NVMe storage. + It supports multiple NVMe SSDs for fast storage, ensuring high-speed data access for large data + volumes associated with AI and data analytics workloads. The PCIe 4.0 lanes enhance connectivity + options, enabling high throughput for both GPUs and storage devices, which reduces latency and + accelerates data processing. + + 6. **Optimized for AI, ML, and HPC Workloads**: The XE8640 is specifically engineered for AI, ML, and + HPC environments, with a hardware configuration that supports large-scale, compute-heavy applications. + It is ideal for deep learning training, model inferencing, data analytics, genomics, and scientific + simulations, all of which require intensive computational resources and fast data processing. + + 7. **Advanced Cooling and Power Efficiency**: Dell’s multi-vector cooling technology enables effective + airflow management within the compact 2U chassis, ensuring that the XE8640 can support high-power + GPUs and CPUs without overheating. High-efficiency power supplies and thermal management capabilities + reduce energy consumption, making the XE8640 both powerful and efficient for data center deployment. + The server’s cooling design is tailored to handle high-performance GPUs, which typically generate + significant heat, ensuring consistent performance and reliability under load. + + 8. **Flexible Storage Options**: The XE8640 supports a mix of SATA, SAS, and NVMe storage options, allowing + for customizable storage configurations based on workload requirements. It can be configured with + up to 10 x 2.5” drives, including up to 4 NVMe drives for high-speed storage, which is beneficial + for data-intensive tasks that require rapid data access and transfer. The flexibility in storage + options allows organizations to tailor their storage solutions for AI/ML, HPC, and data analytics, + balancing capacity and performance as needed. + + 9. **Networking and I/O Flexibility**: The XE8640 includes multiple high-speed network connectivity options, + including 1GbE, 10GbE, and 25GbE ports, allowing for flexible integration into existing data center + infrastructures. It supports additional network cards via PCIe slots, including SmartNICs for offloading + network processing and enhancing network throughput, which is beneficial for large-scale data transfers. + This networking flexibility makes the XE8640 well-suited for distributed AI and HPC environments, + where fast data exchange across nodes is essential. + + 10. **Management and Security with Dell OpenManage**: The XE8640 is managed using Dell’s OpenManage suite, + which provides comprehensive tools for monitoring, managing, and maintaining server operations. + iDRAC9 with Lifecycle Controller allows for remote management, monitoring, and firmware updates, + streamlining IT operations. It includes Dell’s Cyber Resilient Architecture, featuring hardware + root of trust, secure boot, system lockdown, and firmware recovery capabilities, ensuring security + and compliance for sensitive workloads. + + 11. **Scalable and Modular Design**: The XE8640’s modular design allows for flexible configuration options, + enabling organizations to scale GPU and storage resources based on workload demands. As part of + Dell’s Extreme Scale Infrastructure, it is customizable and scalable, allowing organizations to + adapt the server configuration to evolving computational needs in AI and data science. + +In summary, the Dell PowerEdge XE8640 is a high-density, high-performance server tailored for AI, ML, +HPC, and data-intensive applications. Its combination of dual AMD EPYC processors, support for up to +four high-power GPUs, large memory capacity, and flexible storage options make it an ideal choice for +computationally demanding environments. The server’s advanced cooling, scalable design, and Dell’s robust +management tools further enhance its usability in modern data centers, making it a valuable solution +for organizations aiming to accelerate AI and analytics workloads. + +### **Ideal Use Cases** + +* **AI and ML Model Training**: With its high-density GPU support and large memory capacity, the XE8640 + is ideal for training complex AI and machine learning models that require substantial compute and + memory resources. + +* **HPC and Scientific Research**: The server’s dual AMD EPYC processors and multiple GPUs make it suitable + for HPC workloads, including scientific simulations, weather modeling, and genomics research. + +* **Data Analytics and Big Data**: The XE8640’s processing power, high-speed NVMe storage, and high memory + capacity support big data analytics workloads, allowing for fast data processing and insights. + +* **Inference and Real-Time Analytics**: With support for fast GPUs and PCIe 4.0, the XE8640 is also capable + of handling inference workloads and real-time data analytics, crucial for applications like edge computing + and video analytics. diff --git a/docs/accelerated-computing-infrastructure-F5i5800.md b/docs/accelerated-computing-infrastructure-F5i5800.md new file mode 100644 index 00000000..0e7ba1fe --- /dev/null +++ b/docs/accelerated-computing-infrastructure-F5i5800.md @@ -0,0 +1,107 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## F5 i5800 + +The F5 i5800 is a versatile application delivery controller (ADC) that is part of the F5 BIG-IP iSeries. +It is designed to deliver advanced traffic management, security, and application performance optimization, +making it well-suited for large enterprises, service providers, and data centers. This device provides +high performance, flexibility, and support for a range of security and application delivery functions, +ensuring consistent, secure, and optimized user experiences. Here are the key features of the F5 i5800: + + 1. **High Performance and Throughput**: The i5800 offers high performance, with up to 80 Gbps of L4 throughput + and 8 Gbps of SSL bulk encryption throughput, making it capable of handling high volumes of traffic + and complex security requirements. Its high performance is ideal for handling large volumes of + connections in applications that require rapid response times and high availability. + + 2. **Advanced SSL/TLS Offloading**: The i5800 includes dedicated hardware for SSL/TLS offloading, which + allows it to handle encrypted traffic with minimal impact on performance. SSL offloading enables + faster application response times by offloading the cryptographic processing from the application + servers, freeing up server resources and improving user experience. Supports modern encryption + standards, including TLS 1.3, which enhances security for encrypted connections. + + 3. **Comprehensive Application Security**: The F5 i5800 can be equipped with Advanced WAF (Web Application + Firewall) capabilities to protect web applications against various threats, such as SQL injection, + cross-site scripting (XSS), and other OWASP Top 10 vulnerabilities. It includes bot protection and + DDoS mitigation features, safeguarding applications from automated attacks and distributed denial-of-service attacks. IP Intelligence and threat intelligence services are available to provide real-time threat + information, helping to identify and block potentially malicious traffic. + + 4. **Traffic Management with L4-L7 Capabilities**: The i5800 offers comprehensive Layer 4 to Layer 7 traffic + management, enabling intelligent routing, load balancing, and failover capabilities. Advanced load + balancing features, including global server load balancing (GSLB) and local traffic management + (LTM), ensure high availability and optimal distribution of traffic across multiple servers and + data centers. iRules scripting allows for highly customizable traffic management policies, giving + network administrators granular control over traffic behavior and routing. + + 5. **iApps and iControl for Orchestration and Automation**: iApps is F5's application-centric configuration + framework, allowing simplified and automated deployment of application services. iControl REST + APIs enable integration with DevOps tools and support for automation and orchestration, making + it easier to manage complex deployments and integrate with CI/CD pipelines. These features help + organizations streamline application deployment, increase operational efficiency, and reduce configuration + errors. + + 6. **Enhanced Security with Access Policy Manager (APM)**: The i5800 can integrate with Access Policy + Manager (APM), which provides secure, context-based access control and authentication services. + APM enables Single Sign-On (SSO) and multi-factor authentication (MFA) for secure access to applications, + whether hosted on-premises or in the cloud. It also supports Zero Trust principles by verifying + user identity and device posture, allowing for controlled access to sensitive applications. + + 7. **Application Acceleration with TCP Optimization and Caching**: The i5800 provides application acceleration + features, including TCP optimization, which improves the efficiency of TCP connections, reducing + latency and improving application response times. It also supports caching and compression, which + reduces the load on backend servers by storing frequently requested content and compressing responses + for faster delivery to end-users. These features are beneficial for applications with high traffic + demands, enhancing user experience and reducing bandwidth consumption. + + 8. **Programmable and Customizable with iRules and iCall**: iRules allow administrators to customize how + traffic is processed and managed based on specific business logic and application needs. iCall + provides the ability to schedule tasks and execute scripts based on specific events, making it + possible to automate responses to network and application changes. This programmability ensures + flexibility in adapting the ADC to meet unique application requirements and security policies. + + 9. **High Availability and Redundancy**: The i5800 supports active-active and active-passive high availability + (HA) modes, ensuring continuous uptime and minimal service interruptions. With support for failover + and synchronization across multiple units, it provides redundancy for mission-critical applications, + enhancing reliability and resilience against failures. + + 10. **Scalability and Modular Licensing**: F5's modular licensing allows organizations to add new features + and capabilities to the i5800 as their needs evolve, including security, acceleration, and access + features. This flexibility enables organizations to scale their ADC capabilities without needing + to replace the hardware, providing investment protection and cost savings over time. + + 11. **Virtualization Support with F5 Virtual Editions (VEs)**: The i5800 is compatible with F5's Virtual + Editions (VEs), allowing organizations to extend their application delivery and security capabilities + to virtual and cloud environments. With VEs, organizations can implement consistent policies across + on-premises and cloud environments, supporting hybrid and multi-cloud strategies. + + 12. **Network Integration and Compatibility**: The i5800 offers comprehensive support for various networking + environments and can integrate with IPv6, IPsec, VLANs, and VPN configurations. It supports both + standard and high-performance network interfaces, including 1GbE, 10GbE, and 25GbE ports, providing + flexibility for integration into diverse network topologies. The i5800's compatibility with modern + network protocols and interfaces ensures that it can operate effectively within complex network + infrastructures. + +In summary, the F5 i5800 is a high-performance ADC designed to optimize application delivery, provide +robust security, and enhance user experience across diverse network environments. Its features—including +SSL offloading, WAF, advanced traffic management, and programmability with iRules—make it a powerful +solution for organizations seeking to improve application performance, secure applications, and support +high traffic volumes. The i5800’s scalability, modular licensing, and cloud compatibility also make it a +future-proof choice for organizations growing their application infrastructure or adopting hybrid and +multi-cloud architectures. + +### **Ideal Use Cases** + +* **Large Enterprises and Data Centers**: The i5800’s high throughput and SSL offloading make it ideal for + large organizations and data centers that require efficient traffic management and application security. + +* **Service Providers**: With its comprehensive security and traffic management features, the i5800 can + help service providers manage high traffic volumes while ensuring security and optimizing performance + for clients. + +* **E-commerce and Online Services**: The i5800’s WAF, bot protection, and DDoS mitigation features help + protect e-commerce platforms and online services from attacks and provide a secure user experience. + +* **Hybrid Cloud Environments**: The i5800’s integration with F5 VEs enables consistent application security + and delivery across both on-premises and cloud environments, making it suitable for organizations + adopting hybrid or multi-cloud architectures. diff --git a/docs/accelerated-computing-infrastructure-PA5420.md b/docs/accelerated-computing-infrastructure-PA5420.md new file mode 100644 index 00000000..b1d95560 --- /dev/null +++ b/docs/accelerated-computing-infrastructure-PA5420.md @@ -0,0 +1,117 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Palo Alto Networks PA-5420 + +The Palo Alto Networks PA-5420 is a next-generation firewall (NGFW) designed to deliver high-performance +security in enterprise data centers, service providers, and large-scale environments. Part of the Palo +Alto PA-5400 Series, it’s a high-throughput, high-capacity device equipped with features that help secure +networks, prevent advanced threats, and improve overall performance. Here are the key features of the +Palo Alto PA-5420: + + 1. **High Performance and Throughput**: The PA-5420 is built for high-performance environments, with + throughput capabilities designed to handle large volumes of traffic in data centers and enterprise + networks. It offers up to 72 Gbps of firewall throughput and 32 Gbps of Threat Prevention throughput, + allowing it to process large amounts of traffic efficiently even when advanced security features + are enabled. Its performance makes it suitable for handling data-intensive workloads and securing + traffic across multiple high-speed connections. + + 2. **Advanced Threat Prevention**: The PA-5420 integrates Palo Alto’s Threat Prevention services, which + include Intrusion Prevention System (IPS), antivirus, and anti-spyware to detect and block threats + in real-time. It provides multi-layered protection by analyzing traffic for malware, exploits, + and vulnerabilities, preventing threats before they enter the network. The Threat Prevention engine + works alongside other features like WildFire (sandboxing) to detect zero-day threats and unknown + malware. + + 3. **Application-Based Traffic Control with App-ID**: Using Palo Alto’s App-ID technology, the PA-5420 + can accurately identify applications regardless of port, protocol, or encryption. This allows + administrators to set granular policies based on application usage, enabling application-specific + access control and minimizing the attack surface. App-ID also improves visibility by allowing + organizations to monitor and control applications in real-time, enhancing overall security management. + + 4. **User and Content-Based Control with User-ID and Content-ID**: User-ID maps network traffic to specific + users, rather than just IP addresses, allowing for user-based policy enforcement and access control. + Content-ID provides in-line content inspection and control, analyzing traffic for potentially + malicious content or data leakage. It includes URL filtering, data filtering, and file blocking, + which are essential for controlling data usage and mitigating risks associated with malicious or + inappropriate content. + + 5. **SSL Decryption and Inspection**: The PA-5420 has dedicated hardware for SSL decryption, allowing + it to inspect encrypted traffic without significant performance degradation. This capability is + essential for detecting threats hiding within encrypted traffic, which is becoming increasingly + common. By decrypting SSL/TLS traffic, the PA-5420 ensures that threat prevention and content + inspection capabilities extend to encrypted traffic, improving overall security visibility. + + 6. **Integrated WildFire for Advanced Malware Analysis**: WildFire is Palo Alto’s cloud-based threat + intelligence and malware analysis platform that detects unknown and zero-day threats. Suspicious + files are sent to WildFire for sandboxing, where they are executed in a controlled environment + to observe malicious behavior. This enables the PA-5420 to detect and prevent advanced threats + and novel malware variants that have not been previously identified. + + 7. **Scalable and Modular Connectivity Options**: The PA-5420 supports multiple interface types, including + 10GbE, 25GbE, and 40GbE, which provides flexibility in network connectivity and scalability. High-speed + connectivity options make it suitable for integration into modern data centers, supporting large + volumes of data with minimal latency. + + 8. **High Availability and Redundancy**: The PA-5420 supports high availability (HA) configurations, + allowing for redundancy in case of failure. This ensures continuous protection and network uptime. + With active/active and active/passive HA modes, the PA-5420 can be deployed with failover capabilities, + making it reliable for mission-critical applications. + + 9. Comprehensive Security Subscriptions: The PA-5420 can be integrated with Palo Alto’s suite of security + subscriptions, which add a range of advanced capabilities: + + * Threat Prevention: Provides real-time protection from known threats, including malware, exploits, + and command-and-control traffic. + + * URL Filtering: Blocks malicious and unwanted web content based on categories and custom policies. + + * DNS Security: Protects against DNS-based threats, such as domain generation algorithms (DGA), + malware communication, and phishing. + + * GlobalProtect: Extends security policies to remote users and mobile devices, providing a secure + remote access solution. + + * SD-WAN: Optimizes and secures WAN traffic, enabling more flexible and cost-effective branch connections. + + 10. **Automation and Centralized Management**: The PA-5420 integrates with Panorama, Palo Alto’s centralized + management system, enabling network administrators to manage multiple firewalls from a single + interface. It offers APIs for automation, making it compatible with DevOps workflows and enabling + integration with SIEM tools and other third-party security systems. This integration simplifies + policy management, monitoring, and reporting across complex multi-firewall environments. + + 11. **Machine Learning for Autonomous Security**: The PA-5420 utilizes ML-powered capabilities to improve + threat detection and response times, leveraging machine learning models trained on global threat + data. It enables automated policy recommendations, adaptive security, and proactive defense against + emerging threats by constantly learning and adapting to new security challenges. + + 12. **Zero Trust Network Security Capabilities**: The PA-5420 is built with Zero Trust principles in mind, + focusing on enforcing least-privilege access and verifying identity at every stage. Features like + User-ID, App-ID, and SSL decryption contribute to creating a Zero Trust architecture, allowing + for granular control and ensuring only authorized access to sensitive resources. + + 13. **Energy Efficiency and Form Factor**: Designed for high performance and efficiency, the PA-5420 offers + robust security features within a compact form factor. This makes it energy-efficient, which is + important for organizations aiming to reduce operational costs and their carbon footprint in data centers. + +In summary, the Palo Alto Networks PA-5420 is a powerful, high-performance next-generation firewall +designed for large, data-intensive environments. With robust features for advanced threat prevention, +SSL inspection, application control, and high-speed connectivity, it offers a comprehensive security +solution for enterprises and service providers. + +### **Ideal Use Cases** + +* **Enterprise Data Centers**: The PA-5420’s high throughput and advanced threat prevention features make + it ideal for protecting large data centers. + +* **Service Providers and Large Enterprises**: With its scalability and ability to handle high traffic + volumes, the PA-5420 is suited for large enterprises and service providers that need to secure and + segment large, complex networks. + +* **Cloud and Hybrid Environments**: Its integration with Palo Alto’s cloud-delivered services makes it + suitable for hybrid and multi-cloud deployments. + +* **High-Risk Sectors**: Industries requiring stringent security, such as financial services, healthcare, + and government, can benefit from the advanced threat detection, SSL inspection, and content filtering + capabilities. diff --git a/docs/accelerated-computing-infrastructure.md b/docs/accelerated-computing-infrastructure.md new file mode 100644 index 00000000..253735c1 --- /dev/null +++ b/docs/accelerated-computing-infrastructure.md @@ -0,0 +1,29 @@ +# How does Rackspace implement Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Architecture + +Rackspace uses several key devices to support Accelerated Computing: + +### [Cisco Nexus N9K-C93108TC-FX3P](accelerated-computing-infrastructure-CiscoN9K-C93108TC-FX3P.md) + +### [Cisco Nexus N9K-C93180YC](accelerated-computing-infrastructure-CiscoN9K-C93180YC.md) + +### [Cisco WS-C2960X-48TD-L.](accelerated-computing-infrastructure-CiscoWS-C2960X-48TD-L.md) + +### [Dell PowerEdge R7515](accelerated-computing-infrastructure-DellR7515.md) + +### [Dell PowerEdge R7615](accelerated-computing-infrastructure-DellR7615.md) + +### [Dell PowerEdge R7625](accelerated-computing-infrastructure-DellR7625.md) + +### [Dell PowerEdge XE7100](accelerated-computing-infrastructure-DellXE7100.md) + +### [Dell PowerEdge XE8640](accelerated-computing-infrastructure-DellXE8640.md) + +### [HPE ProLiant DL380 Gen9](accelerated-computing-infrastructure-DL380-Gen9.md) + +### [F5 i5800](accelerated-computing-infrastructure-F5i5800.md) + +### [Palo Alto Networks PA-5420](accelerated-computing-infrastructure-PA5420.md) diff --git a/docs/accelerated-computing-overview.md b/docs/accelerated-computing-overview.md new file mode 100644 index 00000000..0da08dc0 --- /dev/null +++ b/docs/accelerated-computing-overview.md @@ -0,0 +1,294 @@ +# What is Accelerated Computing? + +![Rackspace Cloud Software](assets/images/ospc_flex_logo_red.svg){ align=left : style="max-width:175px" } + +## Overview + +Accelerated computing uses specialized hardware called accelerators, such as the following: + +* Graphics Processing Units ([GPUs](https://en.wikipedia.org/wiki/Graphics_processing_unit)) +* Neural Processing Units ([NPUs](https://support.microsoft.com/en-us/windows/all-about-neural-processing-units-npus-e77a5637-7705-4915-96c8-0c6a975f9db4)) +* Smart Network Interface Cards([Smart NICs](https://codilime.com/blog/what-are-smartnics-the-different-types-and-features/)) +* Tensor Processing Units ([TPUs](https://en.wikipedia.org/wiki/Tensor_Processing_Unit)) +* Field Programmable Gate Arrays ([FPGAs](https://en.wikipedia.org/wiki/Field-programmable_gate_array)) + +These accelerators are used to perform computations faster than traditional CPUs alone because they are +designed to handle highly parallel, complex, or data-intensive tasks more efficiently. This makes them +ideal for applications like machine learning, scientific simulations, graphics rendering, and big data +processing. + +## Benefits + +* **Parallel Processing**: Accelerators can perform multiple calculations simultaneously. For example, GPUs + have thousands of cores, allowing them to execute many tasks at once, which is ideal for matrix calculations + common in machine learning. +* **Optimized Architectures**: Each type of accelerator is tailored to specific tasks. GPUs are optimized + for floating-point operations, making them well-suited for image processing and deep learning. TPUs + are specifically designed by Google for neural network computations, while FPGAs can be customized + to accelerate a variety of applications. +* **Energy and Cost Efficiency**: Accelerators can reduce energy usage and costs by performing computations + faster, which is particularly important in data centers and high-performance computing environments. +* **Enhanced Performance in AI and Data-Intensive Workloads**: Accelerated computing has become foundational + for AI and machine learning, where training models on large datasets can take days or weeks without + specialized hardware. + +### GPUs + +GPUs are widely used as accelerators for a variety of tasks, especially those involving high-performance +computing, artificial intelligence, and deep learning. Originally designed for rendering graphics in +video games and multimedia applications, GPUs have evolved into versatile accelerators due to their +highly parallel architecture. Here’s how GPUs act as effective accelerators: + + 1. **Massively Parallel Architecture**: GPUs contain thousands of smaller cores that can execute many operations + simultaneously, making them ideal for tasks that can be broken down into many smaller computations. + This parallelism is especially useful in AI, where tasks like training neural networks require vast + amounts of matrix multiplications and other operations that can run in parallel. + + 2. **High Throughput for Large Data**: For tasks that involve processing large datasets, GPUs can provide + significantly higher throughput than CPUs, allowing faster processing of data. This makes them suitable + for tasks like image and video processing, data analytics, and simulation-based applications (e.g., climate modeling). + + 3. **Efficient for Deep Learning and AI**: GPUs are extremely effective for deep learning tasks. Training + a deep neural network involves extensive matrix calculations, which GPUs can handle with much higher + efficiency than CPUs. Popular machine learning frameworks like TensorFlow, PyTorch, and others have + GPU support, allowing developers to take advantage of GPU acceleration for both training and inference. + + 4. **Real-Time Processing Capabilities**: In applications where low latency is essential, such as autonomous + driving or real-time video processing, GPUs are well-suited due to their ability to process data + quickly. For example, self-driving cars use GPUs to analyze sensor data and make decisions in real-time. + + 5. **Accelerating Scientific Computing**: GPUs are commonly used in scientific research and high-performance + computing (HPC) applications that require intensive computations, such as molecular dynamics, astrophysics + simulations, and genomic analysis. Researchers can achieve faster results, which can be crucial in + fields like pharmacology and climate science. + + 6. **Support for AI Model Inference and Deployment**: After training, AI models need to be deployed to make + predictions (or perform “inference”) on new data. GPUs can accelerate inference in environments like + data centers, edge devices, and even consumer electronics, enabling real-time decision-making in + fields like healthcare, finance, and security. + + 7. **Software Ecosystem**: GPUs, particularly those from NVIDIA, have a strong ecosystem of software tools + and libraries designed to support accelerated computing, such as CUDA, cuDNN, and TensorRT. These + tools provide developers with optimized functions for AI, machine learning, and scientific computing, + making it easier to harness the full power of GPUs. + +In summary, GPUs function as accelerators by leveraging their parallel processing capabilities and high +computational power to speed up a range of data-intensive tasks. They are versatile tools, widely used +across industries for tasks that require rapid, efficient processing of large volumes of data. + +### NPUs + +NPUs are specialized accelerators designed specifically to handle AI and deep learning tasks, especially +neural network computations. They’re highly optimized for the types of mathematical operations used in AI, +such as matrix multiplications and convolutions, making them particularly effective for tasks like image +recognition, natural language processing, and other machine learning applications. Here’s how NPUs function +as powerful accelerators: + + 1. **Optimized for Neural Network Operations**: NPUs are built specifically for the operations common in + neural networks, such as tensor operations and large-scale matrix multiplications. This specialization + allows them to process these tasks more efficiently than general-purpose CPUs or even GPUs, which are + designed for a broader range of functions. + + 2. **Parallelized Processing Units**: NPUs have multiple cores and processing units optimized for high levels + of parallelism. This allows them to handle many small computations simultaneously, which is ideal + for deep learning tasks that involve large datasets and complex computations. + + 3. **Low Power Consumption**: NPUs are typically designed to be energy-efficient, a major benefit for + mobile and edge devices where power availability is limited. This energy efficiency makes them + suitable for deploying AI directly on devices, such as smartphones, cameras, and IoT devices, without + draining battery life. + + 4. **Faster Inference for Real-Time Applications**: NPUs accelerate the inference phase of machine learning, + which is the application of a trained model to new data. This is critical for real-time applications, + such as face recognition, voice assistants, autonomous driving, and augmented reality, where rapid + responses are needed. + + 5. **Offloading from CPUs and GPUs**: By handling neural network processing independently, NPUs reduce the + load on CPUs and GPUs, allowing those resources to be used for other tasks or further improving the + performance of the system. This is especially useful in data centers and edge AI devices where multiple + processes run simultaneously. + + 6. **Integration in a Range of Devices**: NPUs are becoming common in many devices, from mobile phones + (e.g., Apple’s Neural Engine or Google’s Pixel Visual Core) to data center hardware (e.g., Google’s TPU) + and edge devices. This integration allows AI capabilities to be deployed more widely, even in low-power + environments like IoT sensors. + +In summary, NPUs serve as accelerators by providing hardware that is highly efficient at performing the +specific types of calculations used in neural networks, making AI applications faster, more efficient, +and more accessible across devices. + +### Smart NICs + +Smart NICs act as accelerators by offloading and accelerating network-related +tasks, helping to improve the performance of servers in data centers, cloud environments, and high-performance +computing applications. Unlike traditional NICs that only handle basic data transfer, Smart NICs have +onboard processing capabilities, often including dedicated CPUs, FPGAs, or even GPUs, which enable them +to process data directly on the card. Here’s how they function as powerful accelerators: + + 1. **Offloading Network Tasks from the CPU**: Smart NICs can offload network-intensive tasks, such as packet + processing, encryption, load balancing, and firewall management, directly onto the card. This allows + the main CPU to focus on application-specific computations rather than network processing, increasing + overall system efficiency. + + 2. **Accelerating Data Processing**: With processing capabilities on the NIC, Smart NICs can handle tasks + such as data encryption, compression, and even certain types of data analysis. This is particularly + valuable in environments like data centers, where security and data throughput are critical, as it + speeds up data handling without adding load to the main CPU. + + 3. **Programmable Logic (FPGA-Based Smart NICs)**: Many Smart NICs are FPGA-based, meaning they can be + reprogrammed to support specific network functions. This allows them to be tailored for specialized + networking functions or protocols, making them versatile for different use cases. FPGAs on Smart + NICs can adapt to handle evolving protocols or custom requirements, offering flexibility and + future-proofing. + + 4. **Enhanced Network Performance with RDMA**: Smart NICs often support Remote Direct Memory Access (RDMA), + which allows data to be transferred directly between devices’ memory without involving the CPU. + This drastically reduces latency and improves throughput, which is essential for latency-sensitive + applications such as financial trading, high-frequency transactions, and distributed databases. + + 5. **Security Acceleration**: Smart NICs are increasingly used to handle security functions, like encryption, + firewall management, and intrusion detection, directly on the network card. This allows security + checks to be processed in real-time as data moves through the network, reducing the risk of attacks + while maintaining high network speeds. + + 6. **Data Center and Cloud Optimization**: In cloud and data center environments, Smart NICs help handle + the significant networking load generated by virtualized environments and containers. By offloading + and accelerating virtual network functions (VNFs), such as virtual switches and routers, Smart NICs + improve resource utilization and lower the CPU load, supporting more virtual machines or containers + per server. + + 7. **Accelerating Storage Networking**: Smart NICs can accelerate storage networking tasks, such as NVMe + over Fabrics (NVMe-oF), which allows faster access to remote storage. By managing storage access + and data transfer at the NIC level, they help ensure high performance for data-intensive applications. + + 8. **Edge Computing and IoT**: Smart NICs are beneficial for edge devices that process large amounts of + data locally before sending it to the cloud. By performing tasks like data filtering, aggregation, + and compression at the NIC level, they help streamline data transfer and lower latency for edge + computing applications. + +In short, Smart NICs serve as accelerators by processing network and data-related tasks directly on the +network interface card, reducing CPU load, improving network performance, and enabling efficient data +handling. Their ability to offload and accelerate various functions makes them valuable in data-intensive +environments, especially where low latency, high security, and scalability are essential. + +### TPUs + +TPUs are specialized accelerators developed by Google to optimize and accelerate machine learning workloads, +particularly for deep learning and neural network computations. Unlike general-purpose processors, TPUs +are custom-designed to efficiently handle the massive amounts of matrix operations and tensor computations +commonly required by machine learning algorithms, especially deep neural networks. Here’s how TPUs function +as powerful accelerators: + + 1. **Matrix Multiplication Optimization**: TPUs are designed to accelerate matrix multiplications, a core + component of most deep learning models. Neural networks involve extensive matrix operations, and + TPUs are specifically built to execute these computations faster than CPUs or even GPUs, making + them highly efficient for deep learning tasks. + + 2. **High-Level Parallel Processing**: TPUs contain a large number of cores and offer high levels of parallelism, + enabling them to perform many operations simultaneously. This is essential for handling large neural + networks, as the TPU can process thousands of neurons and connections concurrently, leading to faster + training times for complex models. + + 3. **Low Power Consumption**: TPUs are designed to be energy-efficient, making them suitable for large-scale + data centers where power costs are significant. By consuming less power per operation compared to + CPUs or GPUs, TPUs help reduce the overall energy footprint of machine learning infrastructure. + + 4. **High-Speed Memory Access**: TPUs are equipped with a dedicated high-bandwidth memory (HBM) that allows + rapid data access, further accelerating the processing of machine learning workloads. This enables + the TPU to feed data to the processing units without bottlenecks, allowing faster training and inference. + + 5. **Performance for Inference and Training**: TPUs are highly effective for both training models and performing + inference (using trained models to make predictions on new data). For inference, TPUs can deliver low + latency, which is essential for real-time AI applications, such as voice recognition, image classification, + and autonomous driving. + + 6. **Optimized for TensorFlow**: TPUs are tightly integrated with TensorFlow, Google’s open-source machine + learning framework. This integration allows developers to easily leverage TPUs within TensorFlow, + as it provides optimized functions and tools that are compatible with TPU hardware. While they can + work with other frameworks, TensorFlow support is especially efficient. + + 7. **Flexibility with TPU Pods**: In Google Cloud, TPUs are available in clusters called TPU Pods, which + allow scaling up the processing power by interconnecting many TPUs. This is especially useful for + training large models on massive datasets, as TPU Pods provide the scalability needed to handle + enterprise-scale machine learning workloads. + + 8. **Specialized Data Types (e.g., BFloat16)**: TPUs use a reduced precision format, BFloat16, which allows + faster computation with minimal impact on model accuracy. This data format is optimized for neural + network tasks and reduces the memory and processing requirements, allowing the TPU to handle larger + models more efficiently. + + 9. **Edge TPUs for Low-Power Devices**: Google has developed Edge TPUs, designed for use in edge and IoT + devices. Edge TPUs allow machine learning models to be deployed on smaller, low-power devices for + applications like image recognition, language processing, and object detection at the edge, without + needing to send data back to a central server. + +In summary, TPUs serve as highly specialized accelerators for machine learning and AI by optimizing deep +learning tasks like matrix multiplications and tensor operations. Their custom architecture, memory design, +and integration with TensorFlow enable TPUs to deliver high performance for both training and inference, +particularly in large-scale machine learning deployments and real-time AI applications. + +### FPGAs + +FPGAs are highly customizable accelerators that offer unique advantages for specialized computing tasks, +especially in data-intensive fields such as machine learning, financial trading, telecommunications, and +scientific research. FPGAs are programmable hardware that can be configured to perform specific functions +with high efficiency, making them very versatile. Here’s how FPGAs function as powerful accelerators: + + 1. **Customizable Hardware Architecture**: Unlike fixed-function accelerators (like GPUs or TPUs), FPGAs + are reprogrammable, allowing them to be configured for specific tasks or algorithms. This means + that FPGAs can be optimized on a hardware level for particular workloads, like data encryption, + compression, image processing, or neural network inference. + + 2. **High Parallelism for Data-Intensive Tasks**: FPGAs consist of thousands of programmable logic blocks + that can operate independently, enabling high levels of parallelism. This is particularly valuable + in applications that involve data processing pipelines, such as real-time signal processing in + telecommunications or genomics data analysis. + + 3. **Low Latency and Deterministic Performance**: FPGAs offer extremely low latency and predictable, deterministic + performance, which is crucial for real-time applications. For example, in high-frequency trading, + where milliseconds matter, FPGAs can process data and execute algorithms faster than traditional + CPUs or GPUs, which is advantageous for rapid decision-making and transaction execution. + + 4. **Energy Efficiency**: FPGAs can be configured to perform specific tasks in an energy-efficient way, + using only the hardware resources needed for that task. This customization reduces power consumption + and makes FPGAs suitable for energy-sensitive environments, such as edge devices or large-scale data + centers. + + 5. **Flexibility for Evolving Standards and Algorithms**: Since FPGAs are reprogrammable, they offer adaptability + in fields where standards or algorithms change frequently, like networking or machine learning. + For instance, in network infrastructure, FPGAs can be reprogrammed to support new protocols as + they emerge, which provides longevity and flexibility. + + 6. **Accelerating Machine Learning Inference**: While FPGAs are less commonly used for training neural + networks, they are highly effective for inference tasks. By configuring an FPGA to run a specific + neural network model, organizations can deploy it in applications where low latency and high efficiency + are essential, such as object detection or speech recognition on edge devices. + + 7. **Support for Specialized Data Types**: FPGAs can be configured to handle custom data types and bit + widths, which can optimize both memory usage and processing speed for certain applications. For + example, FPGAs can use reduced-precision data formats that reduce computation time while preserving + acceptable accuracy in applications like AI inference. + + 8. **Hardware-Level Security Features**: FPGAs can implement security algorithms directly at the hardware + level, which is useful in applications that require high levels of security, such as encrypted + communications or sensitive data handling. This can include implementing custom cryptographic algorithms + or using the FPGA to protect against certain types of attacks. + + 9. **Real-Time Signal Processing**: FPGAs are widely used in industries like telecommunications, aerospace, + and automotive for real-time signal processing. They can quickly process and filter signals in + applications like radar, image recognition, and 5G communications, where timing and accuracy are critical. + + 10. **Edge Computing and IoT**: FPGAs are increasingly deployed in edge and IoT devices due to their flexibility, + energy efficiency, and ability to perform specific computations on-device. For example, an FPGA + can handle sensor data preprocessing or run an AI inference model directly on the device, reducing + the need for data transmission to the cloud. + + 11. **Integration with Heterogeneous Computing Environments**: FPGAs can work alongside CPUs, GPUs, and other + accelerators in heterogeneous computing environments. For instance, FPGAs may handle preprocessing or + data compression while GPUs manage AI model inference, with CPUs coordinating the overall workload. + This integration can improve performance and resource utilization in complex data center environments. + +In summary, FPGAs function as accelerators by providing highly customizable, low-latency, and energy-efficient +hardware that can be configured to optimize specific tasks. Their reprogrammability and parallel processing +capabilities make FPGAs valuable for specialized applications where flexibility, speed, and efficiency are +essential, from real-time signal processing to low-latency machine learning inference. diff --git a/mkdocs.yml b/mkdocs.yml index f7f779b4..afdfc869 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -250,6 +250,9 @@ nav: - Claim Storm alert: ovn-alert-claim-storm.md - MariaDB: - Operations: infrastructure-mariadb-ops.md + - Accelerated Computing: + - Overview: accelerated-computing-overview.md + - Infrastructure: accelerated-computing-infrastructure.md - Monitoring and Alerting: - Monitoring Information: monitoring-info.md - Alerting Information: alerting-info.md