SCL-Chan: an asynchronous data-parallel language for irregular algorithms

Parallelism suffers from a lack of programming languages both simple to handle and able to take advantage of the power of present parallel computers. If parallelism expression is too high level, compilers have to perform complex optimizations leading often to poor performances. One the other hand, too low level parallelism transfers difficulties toward the programmer. We propose a programming language that integrates both a synchronous data parallel programming model and an asynchronous execution model. The synchronous data parallel programming model allows safe program design. The asynchronous execution model yields an efficient execution on present MIMD architectures without any program transformation. Our language relies an logical instruction ordering exploited by specific send/receive communications. It allows one to express only the effective data dependences between processors. This ability is enforced by a possible send/receive unmatching, useful for irregular algorithms. A sparse vector computation exemplifies our language potentialities