Trends in Data Locality Abstractions for HPC Systems

The cost of data movement has always been an important concern in high performance computing (HPC) systems. It has now become the dominant factor in terms of both energy consumption and performance. Support for expression of data locality has been explored in the past, but those efforts have had onl...

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Published in:IEEE transactions on parallel and distributed systems Vol. 28; no. 10; pp. 3007 - 3020
Main Authors: Unat, Didem, Dubey, Anshu, Hoefler, Torsten, Shalf, John, Abraham, Mark, Bianco, Mauro, Chamberlain, Bradford L., Cledat, Romain, Edwards, H. Carter, Finkel, Hal, Fuerlinger, Karl, Hannig, Frank, Jeannot, Emmanuel, Kamil, Amir, Keasler, Jeff, Kelly, Paul H. J., Leung, Vitus, Ltaief, Hatem, Maruyama, Naoya, Newburn, Chris J., Pericas, Miquel
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects:
Arrays
Computation
Computer Science
data layout
Data locality
Data structures
Distributed databases
Distributed, Parallel, and Cluster Computing
Energy consumption
high-performance computing
Layout
Libraries
locality-aware runtimes
MATHEMATICS AND COMPUTING
Parallel processing
Productivity
programming abstractions
Trends
data layout
locality-aware runtimes
programming abstractions
Data locality
high-performance computing
ISSN:1045-9219, 1558-2183, 1558-2183
Online Access:Get full text
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Summary:The cost of data movement has always been an important concern in high performance computing (HPC) systems. It has now become the dominant factor in terms of both energy consumption and performance. Support for expression of data locality has been explored in the past, but those efforts have had only modest success in being adopted in HPC applications for various reasons. them However, with the increasing complexity of the memory hierarchy and higher parallelism in emerging HPC systems, locality management has acquired a new urgency. Developers can no longer limit themselves to low-level solutions and ignore the potential for productivity and performance portability obtained by using locality abstractions. Fortunately, the trend emerging in recent literature on the topic alleviates many of the concerns that got in the way of their adoption by application developers. Data locality abstractions are available in the forms of libraries, data structures, languages and runtime systems; a common theme is increasing productivity without sacrificing performance. This paper examines these trends and identifies commonalities that can combine various locality concepts to develop a comprehensive approach to expressing and managing data locality on future large-scale high-performance computing systems.
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USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
German Research Foundation (DFG)
AC04-94AL85000; AC02-06CH11357; AC02-05CH11231
SAND-2017-3844J
ISSN:1045-9219
1558-2183
1558-2183
DOI:10.1109/TPDS.2017.2703149