CUDA C++ Best Practices Guide - NVIDIA Developer

cuda C++ best Practices Guide Design Guide | January 2022. Table of Contents What Is This Document?.. viii Who Should Read This Guide ?..viii Assess, Parallelize, Optimize, ix x Recommendations and best Chapter 1. Assessing Your Chapter 2. Heterogeneous 2. Differences between Host and What Runs on a cuda -Enabled Device?..3. Chapter 3. Application 5. Creating the Identifying Understanding 6. Strong Scaling and Amdahl's Weak Scaling and Gustafson's Applying Strong and Weak Chapter 4. Parallelizing Your Chapter 5. Getting 9. Parallel 9. Parallelizing 9. Coding to Expose 10. Chapter 6. Getting the Right 11. 11. Reference Unit Numerical Accuracy and Single vs. Double 12. Floating Point Math Is not cuda C++ best Practices Guide | ii IEEE 754 13. x86 80-bit 13. Chapter 7. Optimizing cuda 14. Chapter 8. Performance 15. 15. Using CPU Using cuda GPU 16. Theoretical Bandwidth 17. Effective Bandwidth 17. Throughput Reported by Visual 18. Chapter 9. Memory Data Transfer Between Host and 19.

CUDA C++ Best Practices Guide DG-05603-001_v11.6 | x Parallelize Having identified the hotspots and having done the basic exercises to set goals and expectations, the developer needs to parallelize the code. Depending on the original code, this can be as simple as calling into an existing GPU-optimized library such as cuBLAS, cuFFT,

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