|Subject:||Re: [Discuss-gnuradio] [VOLK] GPU acceleration -> OpenCL integration?|
|Date:||Sun, 20 Dec 2015 17:51:31 -0500|
Stefan,First off I definitely want to encourage investigations of this sort: so even though I have some thoughts similar to Sylvains/Tom's about whether VOLK is the right place to do this, I definitely want to encourage *trying* this, since you never know - we could be entirely wrong about whether or not this will work. The only way to know for sure is to try it.That said: I do think there are way *within* VOLK to deal with the issue of the input size (i.e. vector size) having a large impact on performance - namely the custom dispatcher. This is a concept that exists in VOLK, but has larger gone unnoticed because by in the large the default dispatcher does a good (or at least, good-enough) job at selecting the proper proto-kernel. For off-loading concepts such as utilizing GPU's via OpenCL, a custom dispatcher *could* select the appropriate proto-kernel (including directing the OpenCL implemention to select a CPU vs. GPU-based implementation, if multiple OpenCL implementations are available) on a per-'work()' call from the GNURadio scheduler. In other words, instead of relying on volk_profile to select the best proto-kernel for all calls to that particular volk kernel, the dispatcher could have something more akin to the FFTW 'wisdom' where for different sizes of matrices/vectors, different proto-kernels are called (including the CPU SIMDized call, instead of the OpenCL call for smaller input sizes, etc.).Anyways - I definitely think this is something that should be looked into more, and if you are interested in pursuing this as - either as a GSoC project or otherwise, I would definitely encourage it, as well as offer assistance/advice where I can.Doug--On Thu, Dec 17, 2015 at 7:58 PM, Stefan Wunsch <address@hidden> wrote:Hi,
On 12/18/2015 12:30 AM, Tom Rondeau wrote:
> On Thu, Dec 17, 2015 at 1:14 PM, Sylvain Munaut <address@hidden> wrote:
>>> RUN_VOLK_TESTS: volk_32f_x2_matrix_nxn_multiply_puppet_32f(1000000,10)
>>> generic completed in 28482ms
>>> a_opencl completed in 13364.3ms
>> Question is how does that number change for smaller problem sizes ?
>> And what would be the average problem size encountered in real env.
>> For SIMD optimization the result of "who's the fastest" doesn't vary
>> too much depending on problem size because they don't have much setup
>> / teardown size.
>> For OpenCL I very much doubt that would be the case and if you end up
>> with an app making a lot of "smallish" (and given the default buffer
>> size of GR, I feel the calls to volk aren't processing millions of
>> samples at a time in a single call)
> This is a great start. But Sylvain makes good points about the data
> transfer issue. That's definitely a problem we have to think about. It's
> why we have avoided pursuing GPU support in VOLK in the past. Now, if
> heterogeneous processor technologies change, so might this problem.
> On the other hand, Doug Geiger has made progress on building OpenCL support
> into the buffer structure of the scheduler. What you've done here might
> work better as a block designed around this concept.
I just wondered why it has not been done yet, but I see the problems now
(Sylvain made the point).
If a proper device selection and initialization is integrated into VOLK,
probably the same processings could be used for the scheduler (e.g.,
with a generic fallback). But as well, I think that I don't know enough
about all of this ;)
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