GPU Computing offers immense computing capabilities - but to leverage it requires Parallel Thinking.

The most complex part of the process of implementing a new algorithm or porting existing code to use GPU Computing is  the process of  reviewing your program's architecture  to find parallel processing opportunities . The final step of moving data and launching 1000's of threads using CUDA or other languages and API rarely represents more than 20% of the total effort. Its possible that your application may use numeric libraries or other compute intensive libraries or code which may already been enhanced to use CUDA, check out our Getting Started Guide and also our Tools & Ecosystem pages for additional information.

CUDA has been widely adopted throughout the world as the most accessible and intuitive way to achieve massive parallelism - and this is reflected by large number of Universities which include CUDA as part of their standard curriculum. See the growing number of CUDA Centers around the world.

CUDA Webinars
CUDA Courses Online 
CUDA Courses Around the World
CUDA Teaching Centers
CUDA Books
CUDA Activities

Educate yourself by attending CUDA and Parallel Computing Courses offered by insitutions around the world,  or training seminars and workshops offered by our many partners. If you are self driven then we have several full courses available online, recording of many presentations and webinars, a wealth of documentations and samples. Several books are now available which guide the reader through the process of thinking parallel and optimizing CUDA applications.

NVIDIA hosts regular webinars for developers, from basic introductions to CUDA,  overviews of partner products and tools and live Q&A with engineering teams - some of these webinars are open to everyone , others are exclusive to our registered developers. 

Our CUDA in Action pages also contains  research papers and applications, in almost every domain.

Learn more about programming GPUs and tools/libraries, check out the GPU Technology Conference 2010 sessions on:

   – High Performance Computing
   – Programming Languages & Techniques
   – Tools & Libraries