Re:Using Intel’s Xeon Phi for Brain Research Visualization
by dibanez on Sunday July 31, 2016 @05:40PM
(#12199025)
As someone who has programmed both Phis and conventional x86 CPUs, I can confirm that the Phi is more sensitive to data traversal order and NUMA effects on which core accesses which memory. Also, the latest generation (Knights Landing) has much better performing cores than the previous generation.
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Re:Using Intel’s Xeon Phi for Brain Research Visualization
by reitzensteinm on Sunday July 31, 2016 @05:45PM
(#12199048)
Well, if it weren't the case and you had that core count without compromise, Phis would have come along a lot sooner with a price tag to match :)
Did you happen to use the Knight's Corner or the new Knight's Landing variant? I'd be quite interested to know how KL stacks up, as naively from the specs it seems like it should be a lot more tolerant with code (but not poor memory access patterns).
Re:Using Intel’s Xeon Phi for Brain Research Visualization
by dibanez on Sunday July 31, 2016 @06:24PM
(#12199224)
Both, and it agrees with your prediction. KNL's cores are each much faster than KNC's cores. A KNC core was over 10X slower than a mainstream CPU core, and a KNL core seems to only be about 4.5X slower (on my particular code). I also get linear OpenMP scaling from 1 to 64 threads on KNL, so the parallelism is all there.