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• W2050364078 abstract "Adaptive resource allocation is becoming an important feature to run parallel and grid applications: to better share space and time according to current workload, to schedule around obstacles as from reservation, to deal with varying system load under time-shared execution, and to deal with lack of accurate predictability on heterogeneous resources. Adaptation is potentially very expensive if total data repartitioning is required. Existing approaches of implementing large numbers of MPI via threads suffer from frequent thread switches, inefficient local communication, and being fixed to the chosen number of threads. Our ATOP middleware provides an approach which uses as many processes as there are processors and partitions and migrates the data, while processing the data per process as one data collection. For the partitioning and migration, we employ the Zoltan load-balancing library which is highly portable and supports a large variety of load-balancing approaches, including those of ParMETIS and Jostle. Exploiting features of Zoltan, we propose pre-partitioning (over-partitioning) of data graphs (reducing adaptation cost down to 25%) but can also flexibly decide to partition from scratch (for cases where over-partitioning does not perform well or where non-fitting numbers of resources need to be chosen)." @default.
• W2050364078 created "2016-06-24" @default.
• W2050364078 creator A5023837262 @default.
• W2050364078 creator A5053878765 @default.
• W2050364078 date "2004-01-01" @default.
• W2050364078 modified "2023-10-14" @default.
• W2050364078 title "ATOP-space and time adaptation for parallel and grid applications via flexible data partitioning" @default.
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• W2050364078 doi "https://doi.org/10.1145/1028613.1028628" @default.
• W2050364078 hasPublicationYear "2004" @default.
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