On 12/18/2015 12:30 AM, Tom Rondeau wrote:
> On Thu, Dec 17, 2015 at 1:14 PM, Sylvain Munaut <246tnt@gmail.com> wrote:
>
>> Hi,
>>
>>> 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)
>>
>>
>> Cheers,
>>
>> Sylvain
>>
>
>
> Stefan,
>
> 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.
>
> Tom
>
Hi,
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 ;)
Greetings
Stefan
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