Calculations & programs for power system networks
Calculations & programs for power system networks
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Active messages: a mechanism for integrated communication and computation
ISCA '92 Proceedings of the 19th annual international symposium on Computer architecture
Scientific computing: an introduction with parallel computing
Scientific computing: an introduction with parallel computing
New methods to color the vertices of a graph
Communications of the ACM
Parallel implementations of the power system transient stability problem on clusters of workstations
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Analysis of large GSPN models: a distributed solution tool
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
A distributed memory parallel Gauss-Seidel algorithm for linear algebraic systems
Computers & Mathematics with Applications
A parallel maximum likelihood algorithm for robot mapping
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Efficient parallel computation of pagerank
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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We describe the implementation and performance of an efficient parallel Gauss-Seidel algorithm that has been developed for irregular, sparse matrices from electrical power systems applications. Although, Gauss-Seidel algorithms are inherently sequential, by performing specialized orderings on sparse matrices, it is possible to eliminate much of the data dependencies caused by precedence in the calculations. A two-part matrix ordering technique has been developed -- first to partition the matrix into block-diagonal-bordered form using diakoptic techniques and then to multi-color the data in the last diagonal block using graph coloring techniques. The ordered matrices often have extensive parallelism, while maintaining the strict precedence relationships in the Gauss-Seidel algorithm. We present timing results for a parallel Gauss-Seidel solver implemented on the Thinking Machines CM-5 distributed memory multi-processor. The algorithm presented here requires active message remote procedure calls in order to minimize communications overhead and obtain good relative speedup.