20161012, 00:19  #1 
Jul 2003
So Cal
3^{2}·233 Posts 
msieve on KNL
I've been playing with msieve linear algebra on Knights Landing cpus. Specifically, each compute node has one Intel(R) Xeon Phi(TM) CPU 7250 @ 1.40GHz. This processor has 68 cores in 34 tiles, each with 4 threads, for a total of 272 threads per node.
I compiled msieve with MPI support using icc with the xMICAVX512 option. This worked just fine. I also tried disabling the ASM instructions and using just the C code to see if the compiler would vectorize using AVX512, but the resultant binary was slightly slower. Trying out different parameters, I get by far the best performance with one MPI process per tile with 8 threads per process. So with one compute node, the best layout is a 2x17 MPI grid with 8 threads. Here is a table of estimated runtimes on a 42.1M matrix: Code:
cores nodes time (hrs) 68 1 444 136 2 233 272 4 131 544 8 83 1088 16 46 2176 32 33 Would explicit use of AVX512 speed up the matmul? 
20161012, 02:33  #2 
Tribal Bullet
Oct 2004
2·29·61 Posts 
Probably, the scattergather instructions could be useful. Using 512bit vectors explicitly in block Lanczos may or may not be faster, the vectorvector operations would need hugely more memory for precomputations.

20161105, 23:03  #3 
Jul 2003
So Cal
3^{2}·233 Posts 
Turns out KNL doesn't like a nearly symmetric grid. In the table above, I had run 544 cores as a 16x17 grid, but instead using an 8x34 grid runs nearly 10% faster. Therefore I have also removed the 2176 core run, which used a 32x34 grid.
Code:
cores nodes time (hrs) 68 1 444 136 2 233 272 4 131 544 8 76 1088 16 46 2176 32 ?? BTW, the last half of the 2,1285 linear algebra was run using the KNL nodes, so it works correctly. 
20161106, 11:45  #4 
Tribal Bullet
Oct 2004
DD2_{16} Posts 
I saw, that was awesome. The maximum grid size is just a definition in the code, but also controls the size of a binary file, so once you change the definition you will be binary incompatible with previous savefiles.
(Just change MAX_MPI_GRID_DIM in common.h) 
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