Locality-Aware Task Scheduling and Data Distribution for OpenMP Programs on NUMA Systems and Manycore Processors

Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distri...

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Published in:	Scientific programming Vol. 2015; no. 2015; pp. 1 - 16
Main Authors:	Muddukrishna, Ananya, Brorsson, Mats, Jonsson, Peter A.
Format:	Journal Article
Language:	English
Published:	Cairo, Egypt Hindawi Publishing Corporation 01.01.2015 John Wiley & Sons, Inc
Subjects:	Application programming interfaces (API) Architectural design Architectural knowledge Benchmarking Computer architecture Data distribution Distributing Improve performance Many-core processors Microprocessors Multiprocessing systems Multitasking Network management Non uniform data Performance degradation Performance enhancement Policies Processor architectures Processors Scheduling Scheduling algorithms Scheduling techniques Software architecture Task scheduling
ISSN:	1058-9244, 1875-919X, 1875-919X
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Abstract	Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers.
AbstractList	Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers. Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and on manycore processors is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor, and we identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers. Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers
Author	Brorsson, Mats Jonsson, Peter A. Muddukrishna, Ananya
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Copyright	Copyright © 2015 Ananya Muddukrishna et al. Copyright © 2015 Ananya Muddukrishna et al.; This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Dynamic circular work-stealing deque Proceedings of the 17th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '05) July 2005 Las Vegas, Nev, USA ACM 21 28 10.1145/1073970.1073974 2-s2.0-32144435090 (32) 2013; 18 Lu Q. Alias C. Bondhugula U. Henretty T. Krishnamoorthy S. Ramanujam J. Rountev A. Sadayappan P. Chen Y. Ngai T.-F. Lin H. Data layout transformation for enhancing data locality on NUCA chip multiprocessors Proceedings of the 18th International Conference on Parallel Architectures and Compilation Techniques (PACT '09) September 2009 IEEE 348 357 10.1109/pact.2009.36 2-s2.0-70449628310 Broquedis F. Clet-Ortega J. Moreaud S. Furmento N. Goglin B. Mercier G. Thibault S. Namyst R. Hwloc: a generic framework for managing hardware affinities in HPC applications Proceedings of the 18th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP '10) February 2010 180 186 10.1109/pdp.2010.67 2-s2.0-77952719747 Muddukrishna A. Podobas A. 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References_xml	– reference: Molka D. Schöne R. Hackenberg D. Müller M. Memory performance and SPEC OpenMP scalability on quad-socket x86_64 systems Algorithms and Architectures for Parallel Processing 2011 7016 Berlin, Germany Springer 170 181 Lecture Notes in Computer Science 10.1007/978-3-642-24650-0_15 – reference: Terboven C. Mey D. Schmidl D. Jin H. Reichstein T. Data and thread affinity in OpenMP programs Proceedings of the Workshop on Memory Access on Future Processors: A Solved Problem? (MAW '08) May 2008 377 384 10.1145/1366219.1366222 2-s2.0-56849098650 – volume: 61 start-page: 222 issue: 2 year: 2012 end-page: 236 ident: 35 article-title: An OpenMP compiler for efficient use of distributed scratchpad memory in MPSoCs – reference: McCool M. Reinders J. Robison A. Structured Parallel Programming: Patterns for Efficient Computation 2012 Elsevier – reference: Schmidl D. Terboven C. an Mey D. Towards NUMA support with distance information OpenMP in the Petascale Era 2011 6665 Berlin, Germany Springer 69 79 Lecture Notes in Computer Science 10.1007/978-3-642-21487-5_6 – volume: 18 start-page: 169 issue: 3-4 year: 2010 end-page: 181 ident: 17 article-title: Enabling locality-aware computations in OpenMP – volume: 26 start-page: 110 issue: 2 year: 2012 end-page: 124 ident: 25 article-title: OpenMP task scheduling strategies for multicore NUMA systems – volume: 18 start-page: 379 year: 2013 end-page: 388 ident: 32 article-title: Topology aware task stealing for on-chip NUMA multi-core processors – reference: Nikolopoulos D. S. Papatheodorou T. S. Polychronopoulos C. D. Labarta J. Ayguade E. Is data distribution necessary in OpenMP? Proceedings of the ACM/IEEE Conference on Supercomputing (CDROM '07) November 2000 47 – reference: Ribeiro C. P. Castro M. Méhaut J.-F. Carissimi A. Improving memory affinity of geophysics applications on NUMA platforms using minas High Performance Computing for Computational Science—VECPAR 2010 2011 6449 Berlin, Germany Springer 279 292 Lecture Notes in Computer Science 10.1007/978-3-642-19328-6_27 – reference: Broquedis F. Clet-Ortega J. Moreaud S. Furmento N. Goglin B. Mercier G. Thibault S. Namyst R. Hwloc: a generic framework for managing hardware affinities in HPC applications Proceedings of the 18th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP '10) February 2010 180 186 10.1109/pdp.2010.67 2-s2.0-77952719747 – reference: Chase D. Lev Y. Dynamic circular work-stealing deque Proceedings of the 17th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '05) July 2005 Las Vegas, Nev, USA ACM 21 28 10.1145/1073970.1073974 2-s2.0-32144435090 – reference: Li Y. Melhem R. Jones A. K. Practically private: enabling high performance CMPs through compiler-assisted data classification Proceedings of the 21st International Conference on Parallel Architectures and Compilation Techniques (PACT '12) September 2012 ACM 231 240 10.1145/2370816.2370852 2-s2.0-84867548843 – volume: 37 start-page: 184 issue: 3 year: 2009 end-page: 195 ident: 38 article-title: Reactive NUCA: near-optimal block placement and replication in distributed caches – reference: Muddukrishna A. Jonsson P. A. Vlassov V. Brorsson M. Locality-aware task scheduling and data distribution on NUMA systems OpenMP in the Era of Low Power Devices and Accelerators 2013 8122 Berlin, Germany Springer 156 170 Lecture Notes in Computer Science 10.1007/978-3-642-40698-0_12 – reference: Broquedis F. Furmento N. Goglin B. Namyst R. Wacrenier P.-A. Dynamic task and data placement over NUMA architectures: an OpenMP runtime perspective Evolving OpenMP in an Age of Extreme Parallelism 2009 5568 Berlin, Germany Springer 79 92 Lecture Notes in Computer Science 10.1007/978-3-642-02303-3_7 – reference: Tilera Tile Processor User Architecture Manual 2012 http://www.tilera.com/scm/docs/UG101-User-Architecture-Reference.pdf – reference: Lu Q. Alias C. Bondhugula U. Henretty T. Krishnamoorthy S. Ramanujam J. Rountev A. Sadayappan P. Chen Y. Ngai T.-F. Lin H. Data layout transformation for enhancing data locality on NUCA chip multiprocessors Proceedings of the 18th International Conference on Parallel Architectures and Compilation Techniques (PACT '09) September 2009 IEEE 348 357 10.1109/pact.2009.36 2-s2.0-70449628310 – reference: Duran A. Teruel X. Ferrer R. Martorell X. Ayguade E. Barcelona OpenMP tasks suite: a set of benchmarks targeting the exploitation of task parallelism in OpenMP Proceedings of the International Conference on Parallel Processing (ICPP '09) September 2009 Vienna, Austria 124 131 10.1109/ICPP.2009.64 – reference: Tousimojarad A. Vanderbauwhede W. A parallel task-based approach to linear algebra Proceedings of the IEEE 13th International Symposium on Parallel and Distributed Computing (ISPDC '14) 2014 IEEE 59 66 – volume: 24 start-page: 2334 issue: 12 year: 2013 end-page: 2343 ident: 27 article-title: Adaptive cache aware bitier work-stealing in multisocket multicore architectures – reference: Dashti M. Fedorova A. Funston J. Gaud F. Lachaize R. Lepers B. Quéma V. Roth M. Traffic management: a holistic approach to memory placement on NUMA systems Proceedings of the 18th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '13) March 2013 ACM 381 394 10.1145/2451116.2451157 2-s2.0-84875650624 – reference: McCurdy C. Vetter J. S. Memphis: finding and fixing NUMA-related performance problems on multi-core platforms Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS '10) March 2010 87 96 10.1109/ispass.2010.5452060 2-s2.0-77952562600 – reference: Wittmann M. Hager G. Optimizing ccNUMA locality for task-parallel execution under OpenMP and TBB on multicore-based systems Computing Research Repository, http://arxiv.org/abs/1101.0093 – reference: Pilla L. L. Ribeiro C. P. Cordeiro D. Méhaut J.-F. 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Snippet	Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing...
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SubjectTerms	Application programming interfaces (API) Architectural design Architectural knowledge Benchmarking Computer architecture Data distribution Distributing Improve performance Many-core processors Microprocessors Multiprocessing systems Multitasking Network management Non uniform data Performance degradation Performance enhancement Policies Processor architectures Processors Scheduling Scheduling algorithms Scheduling techniques Software architecture Task scheduling
Title	Locality-Aware Task Scheduling and Data Distribution for OpenMP Programs on NUMA Systems and Manycore Processors
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