[Numpy-discussion] Dot + add operation

Kevin Sheppard kevin.k.sheppard at gmail.com
Wed Mar 31 07:43:02 EDT 2021


Or just use SciPy's  get_blas_funcs
<https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.blas.get_blas_funcs.html#scipy.linalg.blas.get_blas_funcs>
to access *gemm, which directly exposes this function:

https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.blas.dgemm.html

Kevin


On Wed, Mar 31, 2021 at 12:35 PM Ralf Gommers <ralf.gommers at gmail.com>
wrote:

>
>
> On Wed, Mar 31, 2021 at 2:35 AM Guillaume Bethouart <
> guillaume.bethouart at eshard.com> wrote:
>
>> Is it possible to add a method to perform a dot product and add the
>> result to an existing matrix in a single operation ?
>>
>> Like C = dot_add(A, B, C) equivalent to C += A @ B.This behavior is
>> natively proposed by the Blas *gemm primitive.
>>
>> The goal is to reduce the peak memory consumption. Indeed, during the
>> computation of C += A @ B, the maximum allocated memory is twice the size
>> of C.Using *gemm to add directly the result , the maximum memory
>> consumption is less than 1.5x the size of C.
>> This difference is significant for large matrices.
>>
>> Any people interested in it ?
>>
>
> Hi Guillaume, such fused operations cannot easily be done with NumPy
> alone, and it does not make sense to add separate APIs for that purpose
> because there are so many combinations of function calls that one might
> want to fuse.
>
> Instead, Numba, Pythran or numexpr can add this to some extent for numpy
> code. E.g. search for "loop fusion" in the Numba docs.
>
> Cheers,
> Ralf
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