GPU/Accelarator Programming with OpenMP 4.0: Yet Another Significant Parallel Shift in High-Level Parallel Computing

Play GPU/Accelarator Programming with OpenMP 4.0: Yet Another Significant Parallel Shift in High-Level Parallel Computing
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Another fundamental shift in Parallelism Paradigm? Sure. When was the last time you heard that before?

But seriously, as the number of threads/cores continue to increase, there is a growing pressure on applications to exploit more of the available parallelism in their codes, including coarse-, medium-, and fine-grain parallelism. OpenMP has been one of the dominant shared-memory programming models but is evolving beyond that with a new Mission Statement (no, really!) making it well suited for exploiting medium- and fine-grained parallelism.

OpenMP 4.0 exhibits many of these features to support the next step in both consumer, high-performance and exascale computing, with one of the world's first programming model for high-level language support for GPU/Accelerators and vector SIMD across not 1 but 3 high-level languages: C++, C, and that language whose name we dare not speak, but starts with F.
You can talk to me about anything including C++ (even C and that language that shall remain nameless but starts with F), Transactional Memory, Parallel Programming, OpenMP, astrophysics (where my degree came from), tennis (still trying to see if I can play for a living), travel, and the best food (which I am on a permanent quest to eat).

Michael Wong is the CEO of OpenMP. He is the IBM and Canadian representative to the C++ Standard and OpenMP Committee. And did I forget to say he is a Director of and a VP, Vice-Chair of Programming Languages for Canada's Standard Council. He has so many titles, its a wonder he can get anything done.

Oh, and he chairs the WG21 SG5 Transactional Memory, and is the co-author of a number C++11/OpenMP/TM features including generalized attributes, user-defined literals, inheriting constructors, weakly ordered memory models, and explicit conversion operators. Having been the past C++ team lead to IBM´s XL C++ compiler means he has been messing around with designing C++ compilers for twenty years. His current research interest, i.e. what he would like to do if he had time is in the area of parallel programming, transactional memory, C++ benchmark performance, object model, generic programming and template metaprogramming. He holds a B.Sc from University of Toronto, and a Masters in Mathematics from University of Waterloo.

He has been asked to speak at ACCU, C++Now, Meeting C++, CASCON, and many Universities, research centers and companies, except his own, where he has to listen.

Now he and his wife loves to teach their two children to be curious about everything.
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