Overview of Parallel Programming in C++
Presentation Slides, PDFs, Source Code and other presenter materials are available at:https://github.com/CppCon/CppCon2014
Parallel programming was once considered to be the exclusive realm of weather forecasters and particle physicists working on multi-million dollar super computers while the rest us relied on chip manufacturers to crank out faster CPUs every year. That era has come to an end. Clock speedups have been largely replaced by having more CPUs on a chip. Your typical smart phone now has 2 to 4 cores and your typical laptop or tablet has 4 to 8 cores. Servers have dozens of cores and supercomputers have thousands of cores.
If you want to speed up a computation on modern hardware, you need to take advantage of the multiple cores available. This talk is provides an overview of the parallelism landscape. We'll explore the what, why, and how of parallel programming, discuss the distinction between parallelism and concurrency and how they overlap, and learn about the problems that one runs into. We'll conclude with an overview of existing parallelism technologies in C++ and the future directions being considered for parallel programming in standard C++.
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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