- the first 2/3 of the iterations are divided equally between the cores, large chunks
- the next 1/6 (I think it might have been) of the iterations are divided into smaller chunks and handed out to cores as the cores become available
- the remaining (1/6th?) iterations are handed out to cores individually as they become available.
parallel computing workers number vs. PSO particle number
8 次查看(过去 30 天)
显示 更早的评论
Hi there,
I'm trying to run PSO in Matlab. I have a processor of 64 cores. I'm wondering how I should assign particle numbers for PSO. Is that true that at each iteration if I assign 64*n (n is an integer) particles, there won't be idle workers waiting each other, which brings efficiency compared with non-64*n particles? My simulation time varies from 25-40s per simulation.
0 个评论
采纳的回答
Walter Roberson
2021-8-12
Is that true that at each iteration if I assign 64*n (n is an integer) particles, there won't be idle workers waiting each other
No, that is not true. When you use parfor, the only way to avoid having cores idle waiting for other cores, is use a pool of size 1.
The question becomes how long they are going to wait. The answer to that is going to depend upon the variability in work loads.
When there are sufficient cores:
It is possible in this scheme for cores to run out of individual iterations while one of the original large chunks is still executing.
4 个评论
Walter Roberson
2021-8-12
I would suggest that you experiment with a parpool of 16 that is allocated 4 cores per worker. Use the Cluster Profile manager to reduce number of workers but increase numthreads.
更多回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Particle Swarm 的更多信息
产品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!