Optimally Maximizing Iteration-Level Loop Parallelism

Loops are the main source of parallelism in many applications. This paper solves the open problem of extracting the maximal number of iterations from a loop to run parallel on chip multiprocessors. The authors' algorithm solves it optimally by migrating the weights of parallelism-inhibiting dependences on dependence cycles in two phases. First, they model dependence migration with retiming and formulate this classic loop parallelization into a graph optimization problem, i.e., one of finding retiming values for its nodes so that the minimum nonzero edge weight in the graph is maximized.

Provided by: Institute of Electrical & Electronic Engineers Topic: Big Data Date Added: Mar 2012 Format: PDF

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