PetaBricks: a language and compiler for algorithmic choice

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 coarsegrained, library level selections or hand coded cutoffs between base cases and recursive cases. We present PetaBricks, a new implicitly parallel language and compiler where having multiple implementations of multiple algorithms to solve a problem is the natural way of programming. ...

• Type: Conference
• Year: 2009
• Where: PLDI
• Authors: Jason Ansel, Cy P. Chan, Yee Lok Wong, Marek Olszewski, Qin Zhao, Alan Edelman, Saman P. Amarasinghe
• Keywords: Algorithmic Choice, Compiler, PetaBricks Compiler, PLDI 2009, Programming Languages