PaCT '95 Proceedings of the 3rd International Conference on Parallel Computing Technologies
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
The university of Florida sparse matrix collection
ACM Transactions on Mathematical Software (TOMS)
Dynamic Network Information Collectionfor Distributed Scientific Application Adaptation
HiPC '02 Proceedings of the 9th International Conference on High Performance Computing
Asynchronous invocation of adaptations in electronic structure calculations
Proceedings of the 19th High Performance Computing Symposia
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Distributed cluster environments are becoming popular platforms for high performance computing in lieu of single-vendor supercomputers. However, the reliability and sustainable performance of a cluster are difficult to ensure since the amount of available distributed resources may vary during the application execution. To increase robustness, an application needs to have self-adaptive features that are invoked at the runtime. For a class of computationally-intensive distributed scientific applications, iterative linear system solutions, we show a benefit of the adaptations that change the amount of local computations based on the runtime performance information. A few strategies for efficient exchange of such information are discussed and tested on two cluster architectures.