Welcome To The PS3cluster Guide Our community guide allows you to set up your own MPI (Message Passing Interface) based supercomputer cluster with the Playstation 3. This guide was co-written by Gaurav Khanna, based on his previous work on the Gravity Grid and is a current run-time environment for the research of co-author (Chris Poulin), based on his current work in distributed pattern recognition. As such, we currently utilize the Fedora Core for this infrastructure and illustrate a "how-to" below. NOTE: We focus on the Fedora 8 distribution, due to prevalence of Fedora and its Cell SDK (3.0) compatibility. Finally, this content should be considered open source, and here is the license.
CUDA lets you work with familiar programming concepts while developing software that can run on a GP This is the first of a series of articles to introduce you to the power of CUDA -- through working code -- and to the thought process to help you map applications onto multi-threaded hardware (such as GPUs) to get big performance increases. Of course, not all problems can be mapped efficiently onto multi-threaded hardware, so part of my thought process will be to distinguish what will and what won't work, plus provide a common-sense idea of what might work "well-enough". "CUDA programming" and "GPGPU programming" are not the same (although CUDA runs on GPUs). CUDA permits working with familiar programming concepts while developing software that can run on a GPU. It also avoids the performance overhead of graphics layer APIs by compiling your software directly to the hardware (GPU assembly language, for instance), thereby providing great performance.