GLSL Hacker 0.5.0 (Windows / Mac OS X / Linux)
We've just released the CUDA C Programming Best Practices Guide. This guide is designed to help developers programming for the CUDA architecture using C with CUDA extensions implement high performance parallel algorithms and understand best practices for GPU Computing. Chapters on the following topics and more are included in the guide: * Introduction to Parallel Computing with CUDA * Performance Metrics * Memory Optimizations * Execution Configuration Optimizations * Instruction Optimizations * Control Flow * Debugging * Numerical Accuracy and Precision * Performance Optimization StrategiesThis will be included with the 2.3 toolkit, but we decided to release it now because it's definitely worthwhile reading for any CUDA C developer (a lot of collected internal wisdom on proven optimization strategies, for example). Feel free to post any questions or comments in this thread.