191–194 of 194 posts
Aren’t JIT languages at a disadvantage since they are benchmarked through the CLI rather than using a benchmarking library to allow JIT to warmup?
https://www.oracle.com/java/technologies/security-in-java.ht...
Why should that run time startup cost be ignored?
Doesn’t include Prolog which has decent constraint solver answers for n-queens and sudoku, which are pretty fast but I don’t know how they would compare in benchmarks: https://www.metalevel.at/queens/ https://www.metalevel.at/sudoku/
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No, multi-threaded OpenBLAS improves performance to 0.15s.
I dunno man. My claim was that for specific cases with unique properties, it's not hard to beat BLAS, without getting too exotic with your code. BLAS doesn't have routines for multiplies with non-contiguous data, various patterns of sparsity, mixed precision inputs/outputs, etc. The example I gave is for a specific case close-ish to the case I cared about. You're changing it to a very different case, presumably one t…
Earlier quoted context omitted.
The compilation command errors out for me: /home/bjourne/p/laser/benchmarks/gemm/gemm_bench_float32.nim(77, 8) Warning: use `std/os` instead; ospaths is deprecated [Deprecated] /home/bjourne/p/laser/benchmarks/gemm/gemm_bench_float32.nim(101, 8) template/generic instantiation of `bench` from here /home/bjourne/p/laser/benchmarks/gemm/gemm_bench_float32.nim(106, 21) template/generic instantiation of `gemm_nn_fallback`…
Ah, It was from an older implementation that wasn't compatible with Nim v2. I've commented it out. If you pull again it should work. > Anyway the reason for your competitive performance is likely that you are benchmarking with very small matrices. OpenBLAS spends some time preprocessing the tiles which doesn't really pay off until they become really huge. I don't get why you think it's impossible to reach BLAS speed.…