| Autor: |
Hummelgren, Lars, Wikman, John, Eriksson, Oscar, Haller, Philipp, Broman, David |
| Rok vydání: |
2022 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
Efficient parallelization of algorithms on general-purpose GPUs is essential in many areas today. However, it is a non-trivial task for software engineers to utilize GPUs to improve the performance of high-level programs in general. Although many domain-specific approaches are available for GPU acceleration, it is difficult to accelerate existing high-level programs without rewriting parts of the programs using low-level GPU code. We present a compiler implementation using an alternative approach called expression acceleration. This approach marks expressions for acceleration, and the compiler automatically infers which dependent code needs to be accelerated. We design and implement a compiler supporting expression acceleration for a statically typed functional language and evaluate its applicability and performance. |
| Databáze: |
arXiv |
| Externí odkaz: |
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