cjolivier01 commented on issue #9545: Profiling discussion URL: https://github.com/apache/incubator-mxnet/issues/9545#issuecomment-360680487 Question: _"Operator tuning: I saw you have contributed to the operator tuning of mxnet. Seems it will create many omp threads before executing graph. How does this function affect the performance of mxnet? If I have set cpu affinity in my environment, these omp threads will be binded to each core. Then when executing computation graph, many other omp threads will be created and binded again. Do you think that will impact the performance?"_ @cjolivier01: So yes, the graph executor itself will be a couple of threads that execute the operators which tend to, in turn, fork into many OMP threads for some parts of the operation (in some cases). Operator tuning actually supresses this for some cases where the overhead of forking and converging the OMP threads takes longer than it would have taken to just do the whole operation on a single core. This is much more pronounced on non-Intel-OMP libraries (ie libgomp). But anyway, your question is about does the execution thread binded to a core cause the binded OMP thread to be slower due to caching concerns? I'd answer "maybe, but without data to the contrary, I assume that since the execution thread tends to be stalled while the operator is running its omp threads, that it's worse to reserve a whole core that will be idle while N-1 OMP threads run". ^^ this assumes multiple operators are not running in parallel, which is a whole other discussion as it relates to core binding. I am by no means steadfast in this opinion, but it is an assumption at this point. Have you known this to be the case with other frameworks or experiments?
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