Portal: A High-Performance Language and Compiler for Parallel N-Body Problems

Abstract

There is a big gap between the algorithm one designs on paper and the code that runs efficiently on a parallel system. Our goal is to combine the body of work in compilers, performance optimization, and the domain of N-body problems to build a system where domain scientists can write programs at a high level while attaining performance of code written by experts at the low level. This paper presents Portal, a domain-specific language and compiler designed to enable high-performance implementations of N-body problems on modern multicore systems. Our goal in the development of Portal is three-fold, (a) to implement scalable, fast algorithms that have O(n log n) and O (n) complexity, (b) to design an intuitive language to enable rapid implementations of a variety of problems, and (c) to enable parallel large-scale problems to run on multicore systems. We target N-body problems in various domains from machine learning to scientific computing that can be expressed in Portal to obtain an out-of-the-box optimized parallel implementation. Experimental results on 6 N-body problems show that Portal is within a factor of 5% on average of expert hand-optimized C++ code on a dual-socket AMD EPYC processor. To our knowledge, there are no known libraries or frameworks that implement parallel asymptotically optimal algorithms for the class of generalized N-body problems and Portal aims to fill this gap. Moreover, the Portal language and intermediate algorithm representation are portable and easily extensible to different platforms.