12 GPU languages: Getting down to basics
This chapter covers
- Understanding the current landscape of native GPU languages
- Creating simple GPU programs in each language
- Tackling more complex multi-kernel operations
- Porting between various GPU languages
This chapter covers lower-level languages for GPUs. We call these native languages because they directly reflect features of the target GPU hardware. We cover two of these languages, CUDA and OpenCL, that are widely used. We also cover HIP, a new variant for AMD GPUs. In contrast to the pragma-based implementation, these GPU languages have a smaller reliance on the compiler. You should use these languages for more fine-tuned control of your program’s performance. How are these languages different ...
Get Parallel and High Performance Computing now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
