distributed shared-memory (SDSM) provides the abstraction necessary to run shared-memory applications on cost-effective parallel platforms such as clusters of workstations. Howeve...
—Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of data per run, driving the need for storage solutions to im...
Ramya Prabhakar, Sudharshan S. Vazhkudai, Youngjae...
In this paper we address the issue of dependable distributed high performance computing in the field of Symbolic Computation. We describe the extension of a middleware infrastructu...
- Due to the increasing complexity of scientific models, large-scale simulation tools often require a critical amount of computational power to produce results in a reasonable amou...
Workstation clusters are becoming an interesting alternative to dedicated multiprocessors. In this environment, the probability of a failure, during an application's executio...