Hi all,
I'm trying to understand why a server multicore system seems to perform, using a specific scientific application, (much) worse respect to a workstation machine.
At this time I just want to compare the cpu performance of the big and of the small computers in terms of cpu calculation speed, and to do this I have to run a multicore benchmarking suite on the two systems. The problem is that the two machines have a very different number of cores: the small one is Intel and has 6 cores with hyperthreading (so 12 cores are seen by the system) and the other one has 12*4 cores on AMD processors. How would you run a comparison between the two? I believe I should use the same number of cores for each of them, and not use multithreaded code.
Any suggestion on a suite/benchmarks that would be fine? This also means that I should somehow limit the number of cores used by the benchmark on the big machine, and I didn't find any options to do this in the Phoronix test suite documentation.
Any help would be greatly appreciated.
Thank you!
I'm trying to understand why a server multicore system seems to perform, using a specific scientific application, (much) worse respect to a workstation machine.
At this time I just want to compare the cpu performance of the big and of the small computers in terms of cpu calculation speed, and to do this I have to run a multicore benchmarking suite on the two systems. The problem is that the two machines have a very different number of cores: the small one is Intel and has 6 cores with hyperthreading (so 12 cores are seen by the system) and the other one has 12*4 cores on AMD processors. How would you run a comparison between the two? I believe I should use the same number of cores for each of them, and not use multithreaded code.
Any suggestion on a suite/benchmarks that would be fine? This also means that I should somehow limit the number of cores used by the benchmark on the big machine, and I didn't find any options to do this in the Phoronix test suite documentation.
Any help would be greatly appreciated.
Thank you!
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