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
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Abstract	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.
AbstractList	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.
Author	Edwards, H. Carter Hannig, Frank Pericas, Miquel Maruyama, Naoya Hoefler, Torsten Bianco, Mauro Kamil, Amir Cledat, Romain Keasler, Jeff Kelly, Paul H. J. Ltaief, Hatem Dubey, Anshu Newburn, Chris J. Abraham, Mark Chamberlain, Bradford L. Fuerlinger, Karl Finkel, Hal Jeannot, Emmanuel Leung, Vitus Unat, Didem Shalf, John
Author_xml	– sequence: 1 givenname: Didem surname: Unat fullname: Unat, Didem email: dunat@ku.edu.tr organization: Dept. of Comput. Eng., Koc Univ., Istanbul, Turkey – sequence: 2 givenname: Anshu surname: Dubey fullname: Dubey, Anshu email: adubey@anl.gov organization: Argonne Nat. Lab., Lemont, IL, USA – sequence: 3 givenname: Torsten surname: Hoefler fullname: Hoefler, Torsten email: htor@inf.ethz.ch organization: ETH Zurich, Zurich, Switzerland – sequence: 4 givenname: John surname: Shalf fullname: Shalf, John email: jshalf@lbl.gov organization: Lawrence Berkeley Nat. Lab., Berkeley, CA, USA – sequence: 5 givenname: Mark surname: Abraham fullname: Abraham, Mark email: mjab@kth.se organization: KTH R. Inst. of Technol., Solna, Sweden – sequence: 6 givenname: Mauro surname: Bianco fullname: Bianco, Mauro email: mauro.bianco@cscs.ch organization: Swiss Nat. Supercomput. Centre, Lugano, Switzerland – sequence: 7 givenname: Bradford L. surname: Chamberlain fullname: Chamberlain, Bradford L. email: bradc@cray.com organization: Cray Inc., Seattle, WA, USA – sequence: 8 givenname: Romain surname: Cledat fullname: Cledat, Romain organization: Intel Corp., Santa Clara, CA, USA – sequence: 9 givenname: H. Carter surname: Edwards fullname: Edwards, H. Carter email: hcedwar@sandia.gov organization: Sandia Nat. Labs., Albuquerque, NM, USA – sequence: 10 givenname: Hal surname: Finkel fullname: Finkel, Hal email: hfinkel@anl.gov organization: Argonne Nat. Lab., Argonne, IL, USA – sequence: 11 givenname: Karl surname: Fuerlinger fullname: Fuerlinger, Karl email: Karl.Fuerlinger@nm.ifi.lmu.de organization: Ludwig-Maximilians-Univ. Munchen, Munich, Germany – sequence: 12 givenname: Frank surname: Hannig fullname: Hannig, Frank email: frank.hannig@fau.de organization: Univ. of Erlangen-Nuremberg, Erlangen, Germany – sequence: 13 givenname: Emmanuel surname: Jeannot fullname: Jeannot, Emmanuel email: emmanuel.jeannot@inria.fr organization: INRIA Bordeaux Sud-Ouest, Talence, France – sequence: 14 givenname: Amir surname: Kamil fullname: Kamil, Amir email: akamil@umich.edu organization: Univ. of Michigan, Ann Arbor, MI, USA – sequence: 15 givenname: Jeff surname: Keasler fullname: Keasler, Jeff email: keasler1@llnl.gov organization: Lawrence Livermore Nat. Lab., Livermore, CA, USA – sequence: 16 givenname: Paul H. J. surname: Kelly fullname: Kelly, Paul H. J. email: p.kelly@imperial.ac.uk organization: Imperial Coll. London, London, UK – sequence: 17 givenname: Vitus surname: Leung fullname: Leung, Vitus email: vjleung@sandia.gov organization: Sandia Nat. Labs., Albuquerque, NM, USA – sequence: 18 givenname: Hatem surname: Ltaief fullname: Ltaief, Hatem email: Ltaief_hatem@yahoo.fr organization: King Abdullah Univ. of Sci. & Technol., Thuwal, Saudi Arabia – sequence: 19 givenname: Naoya surname: Maruyama fullname: Maruyama, Naoya email: nmaruyama@riken.jp organization: RIKEN, Kobe, Japan – sequence: 20 givenname: Chris J. surname: Newburn fullname: Newburn, Chris J. email: chris.newburn@intel.com organization: Nvidia Corp., Santa Clara, CA, USA – sequence: 21 givenname: Miquel surname: Pericas fullname: Pericas, Miquel email: miquelp@chalmers.se organization: Chalmers Univ. of Technol., Goteborg, Sweden
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Snippet	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...
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SubjectTerms	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
Title	Trends in Data Locality Abstractions for HPC Systems
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