OpenMP False Sharing | 易学教程

问题

I believe I am experiencing false sharing using OpenMP. Is there any way to identify it and fix it?

My code is: https://github.com/wchan/libNN/blob/master/ResilientBackpropagation.hpp line 36.

Using a 4 core CPU compared to the single threaded 1 core version yielded only 10% in additional performance. When using a NUMA 32 physical (64 virtual) CPU system, the CPU utilization is stuck at around 1.5 cores, I think this is a direct symptom of false sharing and unable to scale.

I also tried running it with Intel VTune profiler, it stated most of the time is spent on the "f()" and "+=" functions. I believe this is reasonable and doesn't really explain why I am getting such poor scaling...

Any ideas/suggestions?

Thanks.

回答1:

Use reduction instead of explicitly indexing an array based on the thread ID. That array virtually guarantees false sharing.

i.e. replace this

#pragma omp parallel for 
    clones[omp_get_thread_num()]->mse() += norm_2(dedy);

for (int i = 0; i < omp_get_max_threads(); i++) {
     neural_network->mse() += clones[i]->mse();

with this:

#pragma omp parallel for reduction(+ : mse)
     mse += norm_2(dedy);

neural_network->mse() = mse;

回答2:

One way of knowing for sure is looking at cache statistics with a tool like cachegrind :

valgrind --tool=cachegrind [command]

来源：https://stackoverflow.com/questions/9027653/openmp-false-sharing

标签

c++

c++11

openmp

false-sharing