Fault-Tolerance, Malleability and Migration for Divide-and-Conquer Applications on the Grid
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
A taxonomy of market-based resource management systems for utility-driven cluster computing
Software—Practice & Experience
Selfish Grids: Game-Theoretic Modeling and NAS/PSA Benchmark Evaluation
IEEE Transactions on Parallel and Distributed Systems
A simulator for adaptive parallel applications
Journal of Computer and System Sciences
Satin: A high-level and efficient grid programming model
ACM Transactions on Programming Languages and Systems (TOPLAS)
Jade: a parallel message-driven java
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
A simulator for parallel applications with dynamically varying compute node allocation
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Supporting malleability in parallel architectures with dynamic CPUSETs mapping and dynamic MPI
ICDCN'10 Proceedings of the 11th international conference on Distributed computing and networking
EuroPVM/MPI'06 Proceedings of the 13th European PVM/MPI User's Group conference on Recent advances in parallel virtual machine and message passing interface
Elastic Scalable Cloud Computing Using Application-Level Migration
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
A system framework and API for run-time adaptable parallel software
Proceedings of the 2013 Research in Adaptive and Convergent Systems
Efficient multiprogramming for multicores with SCAF
Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture
Hi-index | 0.00 |
Malleable jobs are parallel programs that can change thenumber of processors on which they are executing at run time in response to an external command.One of the advantages of such jobs is that a job scheduler for malleable jobs can provide improved system utilization and average response time over a scheduler for traditional jobs.In this paper, we present a programming system for creating malleable jobs that is more general than other current malleable systems. In particular, it is not limited to the master-worker paradigmor the Fortran SPMD programming model, but can also support general purpose parallel programs including those written in MPI and Charm++, and has built-in migration and load-balancing, among other features.