GPU architectures and OpenCL: What's important and why? Seminar by David Black-Schaffer, Uppsala University
AbstractToday everyone is positioning GPUs for general purpose computing. They claim that you can get 10-100x speedups over conventional CPUs, and sometimes they're even right. However, to get the most out of current- (and next-) generation GPUs, one needs to understand the architectural differences and how they effect your choice of algorithm. In this talk I will cover GPU architecture in comparison to current CPUs, discuss the implications for getting good performance, and introduce OpenCL as a general-purpose programming language for accessing GPUs and CPUs today.BioDavid Black-Schaffer received his PhD in electrical engineering from Stanford University in 2008 focusing on parallel programming systems for many-core processors. After that he worked for at Apple designing and developing the first implementation of the new OpenCL specification for heterogeneous parallel processing on CPUs and GPUs. Since the fall of 2009 he has been working as a postdoctoral researcher in the Uppsala Architecture Research Team at Uppsala University.