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- W2065431209 abstract "K MapReduce (KMR) is a high-performance MapReduce system in the MPI environment, targeting large-scale supercomputers such as the K computer. Its objectives are to ease programming for data-processing and to achieve efficiency by utilizing the large amount of memory available in large-scale supercomputers. In KMR, shuffling operation exchanges key-value pairs in a scalable way by collective communication algorithms utilizing the K's interconnect. Mapping and reducing operations are multi-threaded to achieve even greater efficiency in modern multi-core machines. Sorting is optimized using fixed-length packed keys instead of variable-length raw keys, which is extensively used inside of shuffling and reducing operations. Besides the MapReduce operations, KMR provides routines for collective file reading for affinity-aware optimizations. This paper presents the results of experimental performance studies of KMR on the K computer. Affinity-aware file loading improves the performance by about 42% over a non-optimized implementation. We also show how KMR can be used to program real-world scientific applications such as meta-genome search and replica-exchange molecular dynamics." @default.
- W2065431209 created "2016-06-24" @default.
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- W2065431209 date "2013-09-01" @default.
- W2065431209 modified "2023-09-27" @default.
- W2065431209 title "K MapReduce: A scalable tool for data-processing and search/ensemble applications on large-scale supercomputers" @default.
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- W2065431209 doi "https://doi.org/10.1109/cluster.2013.6702663" @default.
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