Hi Jerome,
> -----Original Message-----
> From: [email protected] [mailto:numpy-discussion-
> [email protected]] On Behalf Of Jerome Kieffer
> Sent: Friday, March 27, 2015 8:41 PM
> To: [email protected]
> Subject: Re: [Numpy-discussion] ANN: pyMIC v0.5 released
>
> Interesting project. How close is the C++ kernel needed from OpenCL
> kernels ?
That depends a bit on what the kernel does. If the kernel implements something
really like a dgemm, it is just calling MKL's dgemm routine and passing the
parameters into the routine. If the kernel does more, you would need regular
C/C++ coding (with whatever is needed) plus a threading model such as OpenMP
and TBB.
> Is it directly portable ?
I would say no, just because OpenCL does a lot in terms of parallelization of
the kernel whereas pyMIC only gives you control over data transfer and passing
control over to the coprocessor. Threading and SIMD vectorization then is done
by the compiler and/or the programmers.
> I have tested my OpenCL code (via pyopencl) on the Phi and I did not get
> better performances than the dual-hexacore Xeon (i.e. ~2x slower than a
> GPU).
What type of code are you offloading?
Cheers,
-michael
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