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NVBLAS #23
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@staticfloat I suppose this is going to be the same as MKL. Forwarding 64_ suffixed BLAS functions to the non-suffixed ones. @maleadt Are any init/threading NVBLAS specific APIs that need calling. Those will be needed to added here like we did for MKL in #19 |
No specific APIs to call. One problem is that this BLAS only supports a limited number of functions, and forwards to another blas itself (configurable via environment variables and a configuration file):
This breaks autodetection. Adding some symbol to the list works for suffix detection, but for interface detection that doesn't scale.
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We can make nvblas.conf or the env variable point to the Julia provided openblas. |
@maleadt - Ideally something like this is what we need to try out NVBLAS: https://github.com/JuliaLinearAlgebra/MKL.jl/blob/master/src/MKL.jl#L38 Of course, we'll then find things that don't quite work and perhaps LBT may need to be taught about NVBLAS. I suppose CUDA_jll does not include LAPACK. |
Not a drop-in version like NVBLAS at least. |
Might be interesting to experiment with NVBLAS: https://docs.nvidia.com/cuda/nvblas/index.html
Part of CUDA_jll: https://github.com/JuliaBinaryWrappers/CUDA_jll.jl/blob/44445f650547dd14db177336e488460e56d4f354/src/wrappers/x86_64-linux-gnu.jl#L164-L168
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