A fully parallel algorithm for the symmetric eigenvalue problem
SIAM Journal on Scientific and Statistical Computing
Parallel homotopy algorithm for the symmetric tridiagonal eigenvalue problem
SIAM Journal on Scientific and Statistical Computing
The Laguerre iteration in solving the symmetric tridiagonal eigenproblem, revisited
SIAM Journal on Scientific Computing
A scalable eigenvalue solver for symmetric tridiagonal matrices
Parallel Computing
Performance of hybrid message-passing and shared-memory parallelism for discrete element modeling
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
MPI versus MPI+OpenMP on IBM SP for the NAS benchmarks
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Coastal ocean modeling of the U.S. west coast with multiblock grid and dual-level parallelism
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Terascale spectral element dynamical core for atmospheric general circulation models
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
A distributed divide-and-conquer approach to the paralle tridiagonal symmetric eigenvalue problem
HPCN Europe '95 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
Dual-Level Parallel Analysis of Harbor Wave Response Using MPI and OpenMP
International Journal of High Performance Computing Applications
A parallel QR algorithm for symmetric tridiagonal matrices
IEEE Transactions on Computers - Special issue on parallel processors and processing
An implementation of parallel eigenvalue computation using dual-level hybrid parallelism
ICA3PP'07 Proceedings of the 7th international conference on Algorithms and architectures for parallel processing
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We present a hybrid MPI/OpenMP parallel implementation for the eigenvalues of symmetric tridiagonal matrices on cluster of SMP’s environments. The algorithm is based on a divide-and-conquer method which uses the split-merge technique and Laguerre’s iteration. We study two different implementations of the algorithm: one based on MPI and the other based on a hybrid parallel paradigm with MPI/OpenMP. We take a coarse grain OpenMP approach to parallel implementation for solving the eigenvalues of symmetric tridiagonal submatrices within a SMP node. And dynamic work sharing is used in Laguerre’s iterations. This has two effects: first, the amount of synchronization has been reduced; secondly, this could have an effect on the load balance. In addition, we analyze the communication overhead on two different implementations. An experimental analysis on the DeepComp 6800 shows the hybrid algorithm performs good scalability.