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CppCon 2014: Pablo Halpern 'Decomposing a Problem for Parallel Execution'
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So you want to speed up your computation using multicore parallel execution and you've picked a parallelism framework. What now? Parallelism frameworks give you the tools you need, but they don't actually parallelize the code; that's your job. To take advantage of parallel hardware, you must decompose your computation into tasks that can be computed in parallel. In this session, I'll present a real-world problem (the n-bodies problem) and guide you through several different ways in which it can be decomposed for parallel execution. We'll look at how to achieve scalability, resolve data races, and avoid negative multi-core cache effects. At the end of this session, you should have a conceptual understanding of parallel programming fundamentals that can be applied to a wide range of problems using a variety of frameworks.
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Pablo Halpern has been programming in C++ since 1989 and has been a member of the C++ Standards Committee since 2007. He is currently the Parallel Programming Languages Architect at Intel Corp., where he coordinates the efforts of teams working on Cilk Plus, TBB, OpenMP, and other parallelism languages, frameworks, and tools targeted to C++, C, and Fortran users. Pablo came to Intel from Cilk Arts, Inc., which was acquired by Intel in 2009. During his time at Cilk Arts, he co-authored the paper "Reducers and other Cilk++ Hyperobjects", which won best paper at the SPAA 2009 conference. His current work is focused on creating simpler and more powerful parallel programming languages and tools for Intel's customers and promoting adoption of parallel constructs into the C++ and C standards. He lives with his family in southern New Hampshire, USA. When not working on parallel programming, he enjoys studying the viola, skiing, snowboarding, and watching opera. Twitter handle: @PabloGHalpern
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So you want to speed up your computation using multicore parallel execution and you've picked a parallelism framework. What now? Parallelism frameworks give you the tools you need, but they don't actually parallelize the code; that's your job. To take advantage of parallel hardware, you must decompose your computation into tasks that can be computed in parallel. In this session, I'll present a real-world problem (the n-bodies problem) and guide you through several different ways in which it can be decomposed for parallel execution. We'll look at how to achieve scalability, resolve data races, and avoid negative multi-core cache effects. At the end of this session, you should have a conceptual understanding of parallel programming fundamentals that can be applied to a wide range of problems using a variety of frameworks.
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Pablo Halpern has been programming in C++ since 1989 and has been a member of the C++ Standards Committee since 2007. He is currently the Parallel Programming Languages Architect at Intel Corp., where he coordinates the efforts of teams working on Cilk Plus, TBB, OpenMP, and other parallelism languages, frameworks, and tools targeted to C++, C, and Fortran users. Pablo came to Intel from Cilk Arts, Inc., which was acquired by Intel in 2009. During his time at Cilk Arts, he co-authored the paper "Reducers and other Cilk++ Hyperobjects", which won best paper at the SPAA 2009 conference. His current work is focused on creating simpler and more powerful parallel programming languages and tools for Intel's customers and promoting adoption of parallel constructs into the C++ and C standards. He lives with his family in southern New Hampshire, USA. When not working on parallel programming, he enjoys studying the viola, skiing, snowboarding, and watching opera. Twitter handle: @PabloGHalpern
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