Automatic parallelization of the conjugate gradient algorithm
V Kotlyar, K Pingali, P Stodghill - … , LCPC'95 Columbus, Ohio, USA, August …, 1996 - Springer
V Kotlyar, K Pingali, P Stodghill
Languages and Compilers for Parallel Computing: 8th International Workshop …, 1996•SpringerThe conjugate gradient (CG) method is a popular Krylov space method for solving systems
of linear equations of the form Ax= b, where A is a symmetric positive-definite matrix. This
method can be applied regardless of whether A is dense or sparse. In this paper, we show
how restructuring compiler technology can be applied to transform a sequential, dense
matrix CG program into a parallel, sparse matrix CG program. On the IBM SP-2, the
performance of our compiled code is comparable to that of handwritten code from the PETSc …
of linear equations of the form Ax= b, where A is a symmetric positive-definite matrix. This
method can be applied regardless of whether A is dense or sparse. In this paper, we show
how restructuring compiler technology can be applied to transform a sequential, dense
matrix CG program into a parallel, sparse matrix CG program. On the IBM SP-2, the
performance of our compiled code is comparable to that of handwritten code from the PETSc …
Abstract
The conjugate gradient (CG) method is a popular Krylov space method for solving systems of linear equations of the form Ax = b, where A is a symmetric positive-definite matrix. This method can be applied regardless of whether A is dense or sparse. In this paper, we show how restructuring compiler technology can be applied to transform a sequential, dense matrix CG program into a parallel, sparse matrix CG program. On the IBM SP-2, the performance of our compiled code is comparable to that of handwritten code from the PETSc library at Argonne.
Springer
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