An optimizing compiler for parallel chemistry simulations

Authors:
Jun Cao;Ayush Goyal;Krista A. Novstrup;Samuel P. Midkiff;James M. Caruthers
Affiliations:
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Chemical Engineering, Purdue University, West Lafayette, IN;School of Chemical Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Chemical Engineering, Purdue University, West Lafayette, IN
Venue:
International Journal of Parallel Programming
Year:
2009

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Abstract

Well designed domain specific languages have three important benefits: (1) the easy expression of problems, (2) the application of domain specific optimizations (including parallelization), and (3) dramatic improvements in productivity for their users. In this paper we describe a compiler and parallel runtime system for modeling the complex kinetics of rubber vulcanization and olefin polymerization that achieves all of these goals. The compiler allows the development of a system of ordinary differential equations describing a complex vulcanization reaction or single-site olefin polymerization reaction--a task that used to require months--to be done in hours. A specialized common sub-expression elimination and other algebraic optimizations sufficiently simplify the complex machine generated code to allow it to be compiled--eliminating all but 8.0% of the operations in our largest program and enabling over 60 times faster execution on our largest benchmark codes. The parallel runtime and dynamic load balancing scheme enables fast simulations of the model.