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Petabricks: a language and compiler for algorithmic choice, volume 44 (2009).
| Content Provider | CiteSeerX |
|---|---|
| Author | Ansel, Jason Chan, Cy Lok, Yee Marek, Wong Zhao, Olszewski Qin Edelman, Alan Amarasinghe, Saman |
| Abstract | It is often impossible to obtain a one-size-fits-all solution for high performance algorithms when considering different choices for data distributions, parallelism, transformations, and blocking. The best solution to these choices is often tightly coupled to different architectures, problem sizes, data, and available system resources. In some cases, completely different algorithms may provide the best performance. Current compiler and programming language techniques are able to change some of these parameters, but today there is no simple way for the programmer to express or the compiler to choose different algorithms to handle different parts of the data. Existing solutions normally can handle only coarse-grained, library level selections or hand coded cutoffs between base cases and recursive cases. We present PetaBricks, a new implicitly parallel language |
| File Format | |
| Publisher Date | 2009-01-01 |
| Access Restriction | Open |
| Subject Keyword | Algorithmic Choice Different Algorithm Different Choice Parallel Language Available System Resource High Performance Algorithm Recursive Case Different Architecture Problem Size Library Level Selection Different Part Current Compiler Programming Language Technique Base Case Present Petabricks One-size-fits-all Solution Simple Way Data Distribution |
| Content Type | Text |
