A.3. Appendix Review

We saw how to use atomic compare-and-swap operations to implement a GPU mutex. Using a lock built with this mutex, we saw how to improve our original dot product application to run entirely on the GPU. We carried this idea further by implementing a multithreaded hash table that used an array of locks to prevent unsafe simultaneous modifications by multiple threads. In fact, the mutex we developed could be used for any manner of parallel data structures, and we hope that you’ll find it useful in your own experimentation and application development. Of course, the performance of applications that use the GPU to implement mutex-based data structures needs careful study. Our GPU hash table gets beaten by a single-threaded CPU version of the same code, so it will make sense to use the GPU for this type of application only in certain situations. There is no blanket rule that can be used to determine whether a GPU-only, CPU-only, or hybrid approach will work best, but knowing how to use atomics will allow you to make that decision on a case-by-case basis.