Performance Expectations
One might expect to get an N times speedup when running a program parallelized using OpenMP on a N processor platform. However, this seldom occurs for these reasons:
- When a dependency exists, a process must wait until the data it depends on is computed.
- When multiple processes share a non-parallel proof resource (like a file to write in), their requests are executed sequentially. Therefore each thread must wait until the other thread releases the resource.
- A large part of the program may not be parallelized by OpenMP, which means that the theoretical upper limit of speedup is limited according to Amdahl's law.
- N processors in a symmetric multiprocessing (SMP) may have N times the computation power, but the memory bandwidth usually does not scale up N times. Quite often, the original memory path is shared by multiple processors and performance degradation may be observed when they compete for the shared memory bandwidth.
- Many other common problems affecting the final speedup in parallel computing also apply to OpenMP, like load balancing and synchronization overhead.
Read more about this topic: OpenMP
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