Standard D, Mir D benchmarks against Numpy (BLAS)

[Pavel Shkadzko]

On Thursday, 12 March 2020 at 14:12:14 UTC, jmh530 wrote:
> On Thursday, 12 March 2020 at 12:59:41 UTC, Pavel Shkadzko 
> wrote:
>> [snip]
>
> Looked into some of those that aren't faster than numpy:
>
> For dot product, (what I would just call matrix 
> multiplication), both functions are using gemm. There might be 
> some quirks that have caused a difference in performance, but 
> otherwise I would expect to be pretty close and it is. It looks 
> like you are allocating the output matrix with the GC, which 
> could be a driver of the difference.
>
> For the L2-norm, you are calculating the L2 norm entry-wise as 
> a Froebenius norm. That should be the same as the default for 
> numpy. For numpy, the only difference I can tell between yours 
> and there is that it re-uses its dot product function. 
> Otherwise it looks the same.

Numpy uses BLAS "gemm" and D uses OpenBlas "gemm".