Fix documentation errors in sample_int8

Signed-off-by: Rajeev Rao <[email protected]>

samples/README.md

@@ -9,7 +9,7 @@
 | [sampleDynamicReshape](sampleDynamicReshape) | C++ | ONNX | Digit Recognition With Dynamic Shapes In TensorRT |
 | [sampleFasterRCNN](sampleFasterRCNN) | C++ | Caffe | Object Detection With Faster R-CNN |
 | [sampleGoogleNet](sampleGoogleNet) | C++ | Caffe | Building And Running GoogleNet In TensorRT |
-| [sampleINT8](sampleINT8) | C++ | Caffe | Building And Running GoogleNet In TensorRT |
+| [sampleINT8](sampleINT8) | C++ | Caffe | Performing Inference In INT8 Using Custom Calibration |
 | [sampleINT8API](sampleINT8API) | C++ | Caffe | Performing Inference In INT8 Precision |
 | [sampleMLP](sampleMLP) | C++ | INetwork | “Hello World” For Multilayer Perceptron (MLP) |
 | [sampleMNIST](sampleMNIST) | C++ | Caffe | “Hello World” For TensorRT |

samples/sampleINT8/README.md

@@ -27,7 +27,7 @@
 
 This sample, sampleINT8, performs INT8 calibration and inference.
 
-Specifically, this sample demonstrates how to perform inference in 8-bit integer (INT8). INT8 inference is available only on GPUs with compute capability 6.1 or 7.x. After the network is calibrated for execution in INT8, output of the calibration is cached to avoid repeating the process. You can then reproduce your own experiments with any deep learning framework in order to validate your results on ImageNet networks.
+Specifically, this sample demonstrates how to perform inference in 8-bit integer (INT8). INT8 inference is available only on GPUs with compute capability 6.1 or newer. After the network is calibrated for execution in INT8, output of the calibration is cached to avoid repeating the process. You can then reproduce your own experiments with any deep learning framework in order to validate your results on ImageNet networks.
 
 ## How does this sample work?
 

samples/sampleINT8API/README.md

@@ -21,7 +21,7 @@
 
 ## Description
 
-This sample, sampleINT8API, performs INT8 inference without using the INT8 calibrator; using the user provided per activation tensor dynamic range. INT8 inference is available only on GPUs with compute capability 6.1 or 7.x and supports Image Classification ONNX models such as ResNet-50, VGG19, and MobileNet.
+This sample, sampleINT8API, performs INT8 inference without using the INT8 calibrator; using the user provided per activation tensor dynamic range. INT8 inference is available only on GPUs with compute capability 6.1 or newer and supports Image Classification ONNX models such as ResNet-50, VGG19, and MobileNet.
 
 Specifically, this sample demonstrates how to:
 -   Use `nvinfer1::ITensor::setDynamicRange` to set per tensor dynamic range