Hey all,
I'm getting on the plane in a couple of hours, so this might be the last
you here from me till the middle of the night Europe time.
Karl Rupp <r...@iue.tuwien.ac.at> writes:
> > I suggest we start unifying in a couple of days indeed. I still have a
>> couple of things to merge, essentially having GEMM dynamically generated
>> for some cases and publishing the repo for auto-tuning using pyviennacl.
>> These have to be done soon so that Toby can present some good benchmarks
>> at the talk.
I'm currently struggling to get decent performance out of viennacl-dev
master, even when not doing GEMM. Consider single-precision dense GEMV
using a square matrix and vector with 4096 rows/cols. On the GTX 470 on
krupp2, one execution takes ~0.100s; on the C2050, ~0.106s. Execution
overhead is about 0.0003s. But NumPy with MKL takes only ~0.004s; I know
that krupp2 has an 8(?)-core i7, so (something like) 512 rows/cols per
core, but I still didn't expect the gap to be like that. It's strange,
because my GeForce 610M takes ~0.090s, and my Intel Ivy Bridge M GT2 GPU
takes ~0.001s (at last competitive with MKL, though I'm waiting to test
correctness as I write this). And NumPy with OpenBLAS on my i5 takes
~0.009s. Any hints?
> These are all valid points. What about cropping this 'offset' and use
> something like the following:
>
> namespace viennacl { namespace linalg {
>
> void some_api_function() { ... }
>
> namespace detail
> {
> void some_implementation_detail() { ... }
> }
>
> }}
>
> This would preserve the benefit of a visual separation of public API and
> private implementations, yet remove the 'global' indent offset from the
> source file.
I like this; and indeed is what I tend to do when indentation gets out
of hand.
Best,
Toby
--
Toby St Clere Smithe
http://tsmithe.net
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