support for cublasGemmEx

[William Tambellini]

Hi everybody

I see from
http://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#axzz4YgnUYONY
"
cuBLAS. The cuBLAS library added a new function cublasGemmEx(), which is an extension of cublas<t/>gemm(). It allows the user to specify the algorithm, as well as the precision of the computation and of the input and output matrices. The function can be used to perform matrix-matrix multiplication at lower precision.

Read more at: http://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#ixzz4Ygnv5ePl
"

What would it need for AF to be able to use that ?
Thanks
WT.

[Pavan Yalamanchili]

Hi William,

It depends on the type of data you are using. For 16 bit floats and 8bit signed integers, it will be a bit harder because arrayfire does not yet support those datatypes.

If you are using any other data type (including 8 bit unsigned integers), this is fairly easy to implement both internally and externally. You just need to get the cuda pointer out from arrayfire and pass it to the cublasGemmEx function.

 

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[William Tambellini]

ok thanks.
I suppose there is no sync with openCL so no way to enhance AF API in order to set these option through AF::matmul() ?
Cheers
W.

[Pavan Yalamanchili]

Hi William,

We can have the other backends run in a loop. Alternatively we have header files exposing functions specific to each backend. We could add this function on there.

--

Pavan

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