A hybrid granularity model is proposed for general concurrent solution. It is applied to the triangular factorization of a dense matrix ranging in size from 4 to 1024. Concurrency is achieved at two levels: (1) with small (micro) task granularity and (2) with large (blocked) task granularity. Relevance to a many-processor CRAY X-MP is demonstrated by simulation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25642/1/0000194.pd
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
© 2013 American Physical SocietyThis article introduces a highly parallel algorithm for molecular dy...
A defining challenge for research in computer science and engineering has been the ongoing quest for...
On the multiprocessor vector-supercomputer CRAY X-MP, parallelism—beyond vectorization—can be exploi...
KFA Jülich is one of the largest big-science research centers in Europe. At KFA, computational scien...
Modern supercomputers like CRAY X-MP and CRAY Y-MP achieve their high computing speed by using both ...
A Choleski method is described and used to solve linear systems of equations that arise in large sca...
One of the most important issues in parallel processing is the mapping of workload to processors. Th...
It is anticipated that in order to make effective use of many future high performance architectures,...
For many parallel matrix computations the execution time is determinedby the length of the critical ...
It is anticipated that in order to make effective use of many future high performance architectures,...
Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids...
Molecular Dynamics (MD) simulations are an integral method in the computational studies of material...
This paper is submitted for review to the Parallel Computing special issue for HCW and HeteroPar 16 ...
This paper demonstrates the use of automatic granularity control as part of dynamic load balancing f...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
© 2013 American Physical SocietyThis article introduces a highly parallel algorithm for molecular dy...
A defining challenge for research in computer science and engineering has been the ongoing quest for...
On the multiprocessor vector-supercomputer CRAY X-MP, parallelism—beyond vectorization—can be exploi...
KFA Jülich is one of the largest big-science research centers in Europe. At KFA, computational scien...
Modern supercomputers like CRAY X-MP and CRAY Y-MP achieve their high computing speed by using both ...
A Choleski method is described and used to solve linear systems of equations that arise in large sca...
One of the most important issues in parallel processing is the mapping of workload to processors. Th...
It is anticipated that in order to make effective use of many future high performance architectures,...
For many parallel matrix computations the execution time is determinedby the length of the critical ...
It is anticipated that in order to make effective use of many future high performance architectures,...
Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids...
Molecular Dynamics (MD) simulations are an integral method in the computational studies of material...
This paper is submitted for review to the Parallel Computing special issue for HCW and HeteroPar 16 ...
This paper demonstrates the use of automatic granularity control as part of dynamic load balancing f...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
© 2013 American Physical SocietyThis article introduces a highly parallel algorithm for molecular dy...
A defining challenge for research in computer science and engineering has been the ongoing quest for...