A Stable and Efficient Algorithm for the Rank-One Modification of the Symmetric Eigenproblem
SIAM Journal on Matrix Analysis and Applications
A Divide-and-Conquer Algorithm for the Symmetric TridiagonalEigenproblem
SIAM Journal on Matrix Analysis and Applications
ScaLAPACK user's guide
SIAM Journal on Scientific Computing
ACM Transactions on Mathematical Software (TOMS)
A Fast Scalable Universal Matrix Multiplication Algorithm on Distributed-Memory Concurrent Computers
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Computing Approximate Eigenpairs of Symmetric Block Tridiagonal Matrices
SIAM Journal on Scientific Computing
Hi-index | 0.00 |
This paper discusses and compares several parallelization strategies for tree-structured computations. In particular, we focus on the parallelization of the eigenvector accumulation process in divide-and-conquer eigensolvers, such as the recently developed block divide-and-conquer (BD&C) eigensolver. We describe a model algorithm for evaluating the performance of several parallel variants of this accumulation process, and we develop a block parallel approach which is shown to achieve good speedup in experiments on PC clusters.