http://CppCon.org/ — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/cppcon/cppcon2016 — Parallel programming is a hot topic, and everybody knows that multicore processors and GPUs can be used to speed up calculations. What many people don't realize, however, is that CPUs provide another way to exploit parallelism -- one that predates recent multicore processors, has less overhead, requires no runtime scheduler, and can be used in combination with multicore processing to achieve even more speedup. It's called vector parallelism, and the hardware that implements it goes by brand names like SSE, AVX, NEON, and Altivec. If your parallel program does not use vectorization, you could be leaving a factor of 4 to 16 in performance on the floor. In some ways, Vector programming is easier than thread-based parallel programming because it provides ordering guarantees that more closely resemble serial programming. Without an intuitive framework by which to interpret them, the ordering rules can be confusing, however, and restrictions on vector code that don't apply to thread-parallel code must be kept in mind. In this talk, we'll introduce you to the common elements of most vector hardware, show what kind of C++ code can be automatically vectorized by a smart compiler, and talk about programmer-specified vectorization in OpenMP as well as proposals making their way through the C++ standards committee. You'll understand the rules of vectorization, so that you can begin to take advantage of the vector units already in your CPU. A basic understanding of C++11 lambda expressions is helpful. — Pablo Halpern Intel Corp. Software Engineer Greater Boston Area Pablo Halpern has been programming in C++ since 1989 and has been a member of the C++ Standards Committee since 2007. He is currently an enginneer at Intel Corp., where he works on high-performance computing. As the former chairman of the Parallel Programming Models Working Group at Intel, he coordinated 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 providing compiler support for a new generation of high-performance computing architectures as well aspromoting adoption of parallelism and vectorization constructs into the C++ and C standards. He lives with his family in southern New Hampshire, USA. When not working, he enjoys studying the viola, skiing, snowboarding, and watching opera. Twitter handle: @PabloGHalpern — Videos Filmed & Edited by Bash Films: http://www.BashFilms.com/ *-----* Register Now For CppCon 2022: https://cppcon.org/registration/ *-----*