An integer linear programming based approach for parallelizing applications in on-chip multiprocessors

With energy consumption becoming one of the first-class optimization parameters in computer system design, compilation techniques that consider performance and energy simultaneously are expected to play a central role. In particular, compiling a given application code under performance and energy constraints is becoming an important problem. In this paper, we focus on an on-chip multiprocessor architecture and present a parallelization strategy based on integer linear programming. Given an array-intensive application, our optimization strategy determines the number of processors to be used in executing each nest based on the objective function and additional compilation constraints provided by the user. Our initial experience with this strategy shows that it is very successful in optimizing array-intensive applications on on-chip multiprocessors under energy and performance constraints.