Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel MKL and Apple Accelerate was added to the benchmark today.

Please help to improve the blog post during this weekend. It will be announced in the Reddit.

[1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
[2] http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
[3] http://mir.dlang.io

On Saturday, 24 September 2016 at 07:20:25 UTC, Ilya Yaroshenko wrote:
> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel MKL and Apple Accelerate was added to the benchmark today.
>
> Please help to improve the blog post during this weekend. It will be announced in the Reddit.

Let me run that on a desktop machine before you publish the results, I have a Core i7-6700 w/ 2133 MHz DDR4 RAM here.
Mobile CPU often don't reproduce the same numbers, e.g. https://github.com/dlang/druntime/pull/1603#issuecomment-231543115.

On Saturday, 24 September 2016 at 08:13:22 UTC, Martin Nowak wrote:
> On Saturday, 24 September 2016 at 07:20:25 UTC, Ilya Yaroshenko wrote:
>> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel MKL and Apple Accelerate was added to the benchmark today.
>>
>> Please help to improve the blog post during this weekend. It will be announced in the Reddit.
>
> Let me run that on a desktop machine before you publish the results, I have a Core i7-6700 w/ 2133 MHz DDR4 RAM here.
> Mobile CPU often don't reproduce the same numbers, e.g. https://github.com/dlang/druntime/pull/1603#issuecomment-231543115.

This will be good addition! Thank you!
Please use `dub build ...` and then run report at least 2 times, and choice a better one. GEMM uses CPU cache intensively and OS and other apps may significantly hard the performance. So, it make sense to rerun test if something looks failed.

Benchmark code: https://github.com/libmir/mir/blob/master/benchmarks/glas/gemm_report.d

You can ping at Gitter or open an issue if you need help with Benchmark setup.

Gitter:
https://gitter.im/libmir/public

On 24/09/2016 7:20 PM, Ilya Yaroshenko wrote:
> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel
> MKL and Apple Accelerate was added to the benchmark today.
>
> Please help to improve the blog post during this weekend. It will be
> announced in the Reddit.
>
> [1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
> [2]
> http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
>
> [3] http://mir.dlang.io

For giggles can we get a comparison against dmc for Intel MKL assuming of course it compiles?

On Saturday, 24 September 2016 at 12:08:33 UTC, rikki cattermole wrote:
> On 24/09/2016 7:20 PM, Ilya Yaroshenko wrote:
>> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel
>> MKL and Apple Accelerate was added to the benchmark today.
>>
>> Please help to improve the blog post during this weekend. It will be
>> announced in the Reddit.
>>
>> [1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
>> [2]
>> http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
>>
>> [3] http://mir.dlang.io
>
> For giggles can we get a comparison against dmc for Intel MKL assuming of course it compiles?

Intel MKL is closed source. In the same time I don't think that a compiler makes sense for OpenBLAS, Intel MKL, and Apple Accelerate because their computation kernel source code written in assembler.

On 9/24/16 3:20 AM, Ilya Yaroshenko wrote:
> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel
> MKL and Apple Accelerate was added to the benchmark today.
>
> Please help to improve the blog post during this weekend. It will be
> announced in the Reddit.
>
> [1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
> [2]
> http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
>
> [3] http://mir.dlang.io

Awesome. Good to see that most of the graphs have a nice blue envelope :o). Could you also add a comparison with SciPy? People often say it's just fine for scientific computing.

A few correx:

"The post represents performance benchmark" -> "This post presents performance benchmarks"

"most of numerical" -> "most numerical"

"for example Julia Programing Language" -> "for example the Julia Programing Language"

"Mir GLAS is Generic Linear Algebra Subroutines. It has single generic kernel for all targets, all floating point and complex types." -> "Mir GLAS (Generic Linear Algebra Subroutines) has a single generic kernel for all CPU targets, all floating point types, and all complex types."

"In addition, Mir GLAS Level 3 kernels are not unrolled and produce tiny binary code." -> "In addition, Mir GLAS Level 3 kernels are not unrolled and produce tiny binary code, so they put less pressure on the instruction cache in large applications."

"To add new architecture" -> "To add a new architecture"

"needs to extend small GLAS configuration file" -> "needs to extend one small GLAS configuration file"

"configuration is available for" -> "configurations are available for"

"Mir GLAS has native mir.ndslice interface." -> "Mir GLAS offers a native interface in module mir.ndslice."

"for almost all cases" -> "for virtually all benchmarks and parameters"

"Ilya is IT consultant, statistician. He has experience in distributed High Load services, business process analyses. He is the author of std.experimental.ndslice and Mir founder. He was a GSoC mentor for the D Language Foundation and Mir project." -> "Ilya is an IT consultant with a background in statistics. He has experience in distributed high-load services and business process analyses. He is the creator of the Mir library, including std.experimental.ndslice in the D Standard Library. He mentored a related GSoC project for the D Language Foundation."



Andrei

Also the linkedin photo is much better than the one at the bottom of the benchmark page. -- Andrei

On Saturday, 24 September 2016 at 07:20:25 UTC, Ilya Yaroshenko wrote:
> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark. Intel MKL and Apple Accelerate was added to the benchmark today.
>
> Please help to improve the blog post during this weekend. It will be announced in the Reddit.
>
> [1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
> [2] http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
> [3] http://mir.dlang.io

I think you should put the Mir.GLAS graph in front of all the other graphs, right now they are overlapping on that graph. Would probably look a bit better if Mir.GLAS was in the front

On 9/24/16 8:59 AM, WebFreak001 wrote:
> On Saturday, 24 September 2016 at 07:20:25 UTC, Ilya Yaroshenko wrote:
>> Yesterday I announced [1] blog post [2]  about Mir [3] benchmark.
>> Intel MKL and Apple Accelerate was added to the benchmark today.
>>
>> Please help to improve the blog post during this weekend. It will be
>> announced in the Reddit.
>>
>> [1] http://forum.dlang.org/thread/yhfbuxnrqkiqtvsnvngf@forum.dlang.org
>> [2]
>> http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/glas-gemm-benchmark.html
>>
>> [3] http://mir.dlang.io
>
> I think you should put the Mir.GLAS graph in front of all the other
> graphs, right now they are overlapping on that graph. Would probably
> look a bit better if Mir.GLAS was in the front

Also, one other class of plots that would be informative: performance of all other libraries normalized to Mir. The Y axis would be in percentages with Mir at 100%. Then people can easily see what relative gains to expect. -- Andrei

On Saturday, 24 September 2016 at 12:52:09 UTC, Andrei Alexandrescu wrote:
> Could you also add a comparison with SciPy? People often say it's just fine for scientific computing.

That's just BLAS (so could be mkl, could be openBLAS, could be netlib, etc. just depends on the system and compilation choices) under the hood, you'd just see a small overhead from the python wrapping. Basically, everyone uses a BLAS or Eigen.

An Eigen comparison would be interesting.