Pathway analysis is a powerful tool to study metabolic reaction networks under steady state conditions. An Elementary pathway constitutes a minimal set of reactions that can operate at steady state such that each reaction also proceeds in the appropriate direction. In mathematical terms, elementary pathways are the extreme rays of a polyhedral cone--the solution set of homogeneous equality and inequality constraints. Enumerating all extreme rays--given the constraints--is difficult especially if the problem is degenerate and high dimensional. We present and compare two approaches for the parallel enumeration of extreme rays, both based on the double description method. This iterative algorithm has proven efficient especially for degenerate problems, but is difficult to parallelize due to its sequential operation. The first approach parallelizes single iteration steps individually. In the second approach, we introduce a born/die matrix to store intermediary results, allowing for parallelization across several iteration steps. We test our multicore implementations on a 16 core machine using large examples from combinatorics and biology.
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