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Using OpenMP to Simply Parallelize CPU-Intensive C Code

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Using OpenMP to Simply Parallelize CPU-Intensive C Code
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CC Attribution 2.0 Belgium:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Compute-intensive applications usually benefit hugely from parallelization: running code on multiple CPU cores at the same time. One mechanism to implement such parallelism is to use OpenMP, an official open standard that allows for easy parallelization of existing C or C++ code. The latest OpenMP version (4.0, released summer 2013) also covers offloading to accelerators like GPUs and SIMD. Klaas van Gend will introduce OpenMP, its applicability and usefulness and how to use OpenMP to speed up your code. OpenMP is an official, open standard to specify multi-threading, computational offload (to accelerators like GPGPUs) and SIMD (vectorization). OpenMP is a big topic, it is impossible to cover everything.