Here's what I used while doing an undergrad independent study a couple years ago (except for the books; at the time, books on the subject didn't exist yet): On

Here's what I used while doing an undergrad independent study a couple years ago (except for the books; at the time, books on the subject didn't exist yet): Online Tutorials: Dr. Dobbs - CUDA, Supercomputing For the Masses: http://www.drdobbs.com/high-performance-computing/207200659 http://www.drdobbs.com/high-performance-computing/207200659 GTC Video Tutorials / Presentations: http://www.nvidia.com/object/gpu_technology_conference.html http://www.nvidia.com/object/gpu_technology_conference.html University Courses: GaTech ECE4893 - Multicore and GPU Programming for Video Games (not CUDA specific, but covered): http://users.ece.gatech.edu/lanterma/mpg/ http://users.ece.gatech.edu/lanterma/mpg/ UIUC ECE498AL - Applied Parallel Programming: http://courses.engr.illinois.edu/ece498/al/ http://courses.engr.illinois.edu/ece498/al/ Books: Programming Massively Parallel Processors: http://www.amazon.com/Programming-Massively-Parallel-Processors-Hands-/dp/0123814723/ref=sr_1_1?ie=UTF8&qid=1296443374&sr=8-1 http://www.amazon.com/Programming-Massively-Parallel-Process... CUDA By Example: http://www.amazon.com/CUDA-Example-Introduction-General-Purpose-Programming/dp/0131387685/ref=sr_1_2?ie=UTF8&qid=1296443374&sr=8-2 http://www.amazon.com/CUDA-Example-Introduction-General-Purp... If you decide to go the CUDA route, as opposed to OpenCL, then NVIDIA has a lot of solid documentation that will help you get to a "Hello, World" level pretty quickly. This StackOverflow thread should help if you choose to go with an AMD OpenCL solution: http://stackoverflow.com/questions/780978/opencl-books-tutorials http://stackoverflow.com/questions/780978/opencl-books-tutor.... Personally, I would stick with NVIDIA; they seem much more dedicated to advancing the cause and you have support for both API's.