: Data distribution is one of the key aspects that a parallelizing compiler for a distributed memory architecture should consider, in order to get efficiency from the system. The ...
We solve the problem of computing global conformal parameterizations for surfaces with nontrivial topologies. The parameterization is global in the sense that it preserves the con...
Gaussian elimination and LU factoring have been greatly studied from the algorithmic point of view, but much less from the point view of the best output format. In this paper, we g...
Abstract. CG, SYMMLQ, and MINRES are Krylov subspace methods for solving large symmetric systems of linear equations. CG (the conjugate-gradient method) is reliable on positive-def...
Sou-Cheng T. Choi, Christopher C. Paige, Michael A...
A new class of parallel normalized preconditioned conjugate gradient type methods in conjunction with normalized approximate inverses algorithms, based on normalized approximate f...