Combinatorial algorithms for integrated circuit layout
Combinatorial algorithms for integrated circuit layout
A new approach to effective circuit clustering
ICCAD '92 1992 IEEE/ACM international conference proceedings on Computer-aided design
A parallel bottom-up clustering algorithm with applications to circuit partitioning in VLSI design
DAC '93 Proceedings of the 30th international Design Automation Conference
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Mesh Partitioning: A Multilevel Balancing and Refinement Algorithm
SIAM Journal on Scientific Computing
High Performance Computing in Power System Applications
VECPAR '96 Selected papers from the Second International Conference on Vector and Parallel Processing
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
Kernel k-means: spectral clustering and normalized cuts
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
An adaptive scheme for predicting the usage of grid resources
Computers and Electrical Engineering
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The requirements for significant computational resources imposed by dynamic security assessment applications have led to an increasing interest in the use of parallel and distributed computing technologies. This paper presents an adaptive scheme that involves user-friendly flat application program interfaces for scripting and an object-oriented programming environment for distributed dynamic security assessment implementation. Functional parallelism and data parallelism are supported by each of the message passing interface model and TCP/IP model. Adaptive stochastic-based objectives and conservative parameter prediction techniques are used to produce more efficient data parallelism. Tests for a 39-bus network and a 3872-bus network are reported, and the results of these experiments demonstrate that the proposed scheme is able to execute the distributed simulations on either stand-alone personal computers, cluster systems, or a computational grid infrastructure and provide efficient parallelism for the given environment.