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From Algorithm to Generic, Parallel Code

This presentation starts with a parallel algorithm as it is described in books and turns it into a generic implementation. Multiple options for running the algorithm concurrently based on different technologies (OpenMP, Threading Building Blocks, C++ standard-only) are explored.

Using parallel algorithms seems like an obvious way to improve the performance of operations. However, to utilize more processsing power often requires additional work to be done and depending on available resources and the size of the problem the parallel version may actually take longer than a sequential version. Looking at the actual implementation for an algorithm should clarify some of the tradeoffs.

Showing how a parallel algorithm can be implemented should also demonstrate how such an algorithm can be done when there is no suitable implementation available from the [standard C++] library. As the implementation of a parallel algorithms isn't trivial it should also become clear that using a readily available implementation is much preferable.

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Dietmar Kuhl

Dietmar Kühl is a senior software developer at Bloomberg L.P. working on the data distribution environment used both internally and by enterprise installations at clients. Before joining Bloomberg he has done mainly consulting for software projects in the finance area. He is a regular attendee of the ANSI/ISO C++ standards committee, presents at conferences, and he used to be a moderator of the newsgroup comp.lang.c++.moderated. He frequently answers questions on Stackoverflow.

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