The Performance of Coordinated and Independent Checkpointing
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
Diskless Checkpointing
Process Resurrection: A Fast Recovery Mechanism for Real-Time Embedded Systems
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
Availability Modeling and Analysis on High Performance Cluster Computing Systems
ARES '06 Proceedings of the First International Conference on Availability, Reliability and Security
Algorithm-based fault tolerance applied to high performance computing
Journal of Parallel and Distributed Computing
Super-Scalable algorithms for computing on 100,000 processors
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
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The development of scientific software, reliable and efficient, in distributed computing environments, requires the identification and the analysis of issues related to the design and the deployment of algorithms for high-performance computing architectures and their integration in distributed contexts. In these environments, indeed, resources efficiency and availability can change unexpectedly because of overloading or failure i.e. of both computing nodes and interconnection network. The scenario described above, requires the design of mechanisms enabling the software to "survive" to such unexpected events by ensuring, at the same time, an effective use of the computing resources. Although many researchers are working on these problems for years, fault tolerance, for some classes of applications is an open matter still today. Here we focus on the design and the deployment of a checkpointing/migration system to enable fault tolerance in parallel applications running in distributed environments. In particular we describe details about HADAB, a new hybrid checkpointing strategy, and its deployment in a meaningful case study: the PETSc Conjugate Gradient algortithm implementation. The related testing phase has been performed on the University of Naples distributed infrastructure (S.Co.P.E. infrastructure).