Christopher Rodrigues, Thomas Jablin, Abdul Dakkak, Wen-Mei Hwu
2014 SIGPLAN notices  
Functional algorithmic skeletons promise a high-level programming interface for distributed-memory clusters that free developers from concerns of task decomposition, scheduling, and communication. Unfortunately, prior distributed functional skeleton frameworks do not deliver performance comparable to that achievable in a low-level distributed programming model such as C with MPI and OpenMP, even when used in concert with high-performance array libraries. There are several causes: they do not
more » ... e advantage of shared memory on each cluster node; they impose a fixed partitioning strategy on input data; and they have limited ability to fuse loops involving skeletons that produce a variable number of outputs per input. We address these shortcomings in the Triolet programming language through a modular library design that separates concerns of parallelism, loop nesting, and data partitioning. We show how Triolet substantially improves the parallel performance of algorithms involving array traversals and nested, variable-size loops over what is achievable in Eden, a distributed variant of Haskell. We further demonstrate how Triolet can substantially simplify parallel programming relative to C with MPI and OpenMP while achieving 23-100% of its performance on a 128-core cluster.
doi:10.1145/2692916.2555268 fatcat:dinspgk56rc55c6cfe2x6pptcu