即使 CPU 数量增加，执行时间也会增加，为什么？
Increased Execution TIme even with increased number of CPUs, Why?
我有 运行 HPC 集群上不同数量的 CPU 的相同 C++ 问题大小，但我发现当 CPU 数量增加时，执行时间也会增加。我期望执行时间会显着减少。任何人都可以阐明这个问题吗？
以下是每个 CPU 的执行时间
Number of CPUs Problem size Time (seconds)
1 3000000 15.48
2 3000000 18.2
4 3000000 21.73
8 3000000 40.55
16 3000000 60.14
32 3000000 98.75
我的想法：
- CPU 之间的通信增加过多，导致执行时间增加。
希望这能解释它：
"There are two major factors that influence performance: the speed of the CPUs themselves, and the speed of their access to memory. In a cluster, it’s fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences in the speed of main memory and the cache. Consequently, a good multiprocessing environment should allow control over the “ownership” of a chunk of memory by a particular CPU."
我有 运行 HPC 集群上不同数量的 CPU 的相同 C++ 问题大小，但我发现当 CPU 数量增加时，执行时间也会增加。我期望执行时间会显着减少。任何人都可以阐明这个问题吗？
以下是每个 CPU 的执行时间
Number of CPUs Problem size Time (seconds)
1 3000000 15.48
2 3000000 18.2
4 3000000 21.73
8 3000000 40.55
16 3000000 60.14
32 3000000 98.75
我的想法：
- CPU 之间的通信增加过多，导致执行时间增加。
希望这能解释它：
"There are two major factors that influence performance: the speed of the CPUs themselves, and the speed of their access to memory. In a cluster, it’s fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences in the speed of main memory and the cache. Consequently, a good multiprocessing environment should allow control over the “ownership” of a chunk of memory by a particular CPU."