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Multipartitioning is a strategy for parallelizing computations that require solving 1D recurrences along each dimension of a multi-dimensional array. Previous techniques for multipartitioning yield efficient parallelizations over 3D domains only when the number of processors is a perfect square. This paper considers the general problem of computing multipartitionings for d-dimensional data volumes on an arbitrary number of processors. We describe an algorithm that computes an optimaldoi:10.1109/ipdps.2002.1015501 dblp:conf/ipps/Chavarria-MirandaDFM02 fatcat:iwgp7pc4ljgp5bicbst6oebioy