eschnett / IndexSpaces.jl

Mapping physics quantities onto hardware for efficient parallelization.

IndexSpaces.jl

Mapping physics quantities onto hardware for efficient parallelization.

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TODO *

(CI code coverage is bad because the CI tests don't test the CUDA code; these tests need to be run manually.)

Notes

Run benchmarks:

julia --optimize=3 --project=@. --threads=$(nproc) kernels/bb.jl

Run with profiling:

/usr/local/cuda/bin/ncu -f -o profile --set full --target-processes all env LD_LIBRARY_PATH="/home/eschnett/julia-1.8/lib/julia:$LD_LIBRARY_PATH" ~/julia-1.8/bin/julia --optimize=3 --project=@. --threads=$(nproc) kernels/bb.jl

The juliaup-installed Julia does not work. One cannot extract PTX or SASS while profiling.

CPU vs. GPU terms

Intel Skylake vs. Nvidia Tesla V100 (numbers are estimates)

CPU term	count on CPU	count on GPU	GPU term
SIMD lane	16	32	thread
SMT thread	2	32	warp
superscalar	6	2
OOO	>100	n/a	n/a
thread	40	?	block
core	40	80	SM
node	1	1	GPU
scalar register	?	?	uniform register
SIMD register	2688	5?	register cache
L1 cache	8 kB	256 kB	register
L2 cache	1 MB	100 kB	L1 cache / shared memory
L3 cache	?	?	L2 cache
HBM	n/a	32 GB	memory
memory	192 GB	n/a	host memory
-----------------	--------------	--------------	--------------------------