ARS: an adaptive runtime system for locality optimization

Shared memory programs running on Non-Uniform Memory Access (NUMA) machines usually face inherent performance problems stemming from excessive remote memory accesses. A solution, called the Adaptive Runtime System (ARS), is presented in this paper. ARS is designed to adjust the data distribution at...

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Veröffentlicht in:Future generation computer systems Jg. 19; H. 5; S. 761 - 776
Hauptverfasser: Tao, Jie, Schulz, Martin, Karl, Wolfgang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.07.2003
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ISSN:0167-739X, 1872-7115
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Abstract Shared memory programs running on Non-Uniform Memory Access (NUMA) machines usually face inherent performance problems stemming from excessive remote memory accesses. A solution, called the Adaptive Runtime System (ARS), is presented in this paper. ARS is designed to adjust the data distribution at runtime through automatic page migrations. It uses memory access histograms gathered by hardware monitors to find access hot spots and, based on this detection, to dynamically and transparently modify the data layout. In this way, incorrectly allocated data can be moved to the most appropriate node and hence data locality can be improved. Simulations show that this allows to achieve a performance gain of as high as 40%.
AbstractList Shared memory programs running on Non-Uniform Memory Access (NUMA) machines usually face inherent performance problems stemming from excessive remote memory accesses. A solution, called the Adaptive Runtime System (ARS), is presented in this paper. ARS is designed to adjust the data distribution at runtime through automatic page migrations. It uses memory access histograms gathered by hardware monitors to find access hot spots and, based on this detection, to dynamically and transparently modify the data layout. In this way, incorrectly allocated data can be moved to the most appropriate node and hence data locality can be improved. Simulations show that this allows to achieve a performance gain of as high as 40%.
Author Schulz, Martin
Tao, Jie
Karl, Wolfgang
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  surname: Karl
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  email: karlw@in.tum.de
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Cites_doi 10.1145/237090.237205
10.1145/165939.165944
10.1007/BFb0056494
10.1109/SC.2000.10009
10.1109/ICPP.1997.622557
10.1145/74850.74865
10.1145/369028.369119
10.1109/CCGRID.2002.1017133
10.1142/9789812792037_0001
10.1006/jpdc.1996.0136
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10.1007/10704208_32
10.1109/ICPP.2000.876083
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10.1109/ISCA.1998.694793
10.1016/S0164-1212(98)00008-9
10.1007/3-540-44905-1_9
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Page migration
Shared memory programming on NUMA
Data locality optimization
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References_xml – reference: J.S. Chase, F.G. Amador, E.D. Lazowska, H.M. Levy, R.J. Littlefield, The amber system: parallel programming on a network of multiprocessors, in: Proceedings of the 12th ACM Symposium on Operating System Principles, December 1989, pp. 147–158.
– reference: IEEE Computer Society, IEEE Std 1596–1992: IEEE Standard for Scalable Coherent Interface, The Institute of Electrical and Electronics Engineers Inc., New York, NY, USA, August 1993.
– reference: J. Tao, W. Karl, A tool environment for efficient execution of shared memory programs on NUMA systems, in: Proceedings of the Fourth International Workshop on Advanced Parallel Processing Technologies (APPT’01), Ilmenau, Germany, September 2001, pp. 156–165.
– reference: S.C. Woo, M. Ohara, E. Torrie, J.P. Singh, A. Gupta, The SPLASH-2 programs: characterization and methodological considerations, in: Proceedings of the 22nd Annual International Symposium on Computer Architecture, June 1995, pp. 24–36.
– reference: A. Schuster, L. Shalev, Using remote access histories for thread scheduling in distributed memory system, Technical Report LPCR-9701, Computer Science Department, Technion, Haifa, Israel, January 1997.
– reference: J. Tao, W. Karl, M. Schulz, Visualizing the memory access behavior of shared memory applications on NUMA architectures, in: Proceedings of the 2001 International Conference on Computational Science (ICCS), Lecture Notes in Computer Science, vol. 2074, San Francisco, CA, USA, May 2001, pp. 861–870.
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– reference: .
– reference: M. Schulz, J. Tao, C. Trinitis, W. Karl, SMiLE: an integrated, multi-paradigm software infrastructure for SCI-based clusters, in: Proceedings of the IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid), Berlin, Germany, May 2002.
– reference: M. Schulz, Efficient deployment of shared memory models on clusters of PCs using the SMiLEing HAMSTER approach, in: A. Goscinski, H. Ip, W. Jia, W. Zhou (Eds.), Proceedings of the Fourth International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), World Scientific Publishing, December 2000, pp. 2–14.
– reference: E.D. Granston, H.A.G. Wijshoff, Managing pages in shared virtual memory systems: getting the compiler into the game, in: Proceedings of ACM 1993 International Conference on Supercomputing, Tokyo, Japan, July 1993, pp. 11–20.
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– reference: S. Tandri, T.S. Abdelrahman, Automatic partitioning of data and computations on scalable shared memory multiprocessors, in: Proceedings of the 1997 International Conference on Parallel Processing (ICPP’97), Washington, Brussels, Tokyo, August 1997, pp. 64–73.
– reference: Y.C. Hu, A. Cox, W. Zwaenepoel, Improving fine-grained irregular shared-memory benchmarks by data reordering, in: Proceedings of the SC2000 on High Performance Networking and Computing, Dallas, TX, USA, November 2000, pp. 61–74.
– reference: W. Karl, M. Leberecht, M. Oberhuber, SCI monitoring hardware and software: supporting performance evaluation and debugging, in: SCI Scalable Coherent Interface Architecture and Software for High-Performance Compute Clusters, Lecture Notes in Computer Science, vol. 1734, Springer, Berlin, 1999, Chapter 24, pp. 417–432.
– reference: W.C. Hsieh, M.F. Kaashoek, W.E. Weihl, Dynamic computation migration in DSM system, in: Proceedings of the Supercomputing’96, ACM Press and IEEE Computer Society Press, Pittsburgh, November 1996.
– reference: V. Soundararajan, M. Heinrich, B. Verghese, K. Gharachorloo, A. Gupta, J. Hennessy, Flexible use of memory for replication/migration in cache-coherent DSM multiprocessors, in: Proceedings of the 25th Annual International Symposium on Computer Architecture (ISCA-98), June 1998, pp. 342–356.
– reference: B. Verghese, S. Devine, A. Gupta, M. Rosenblum, OS support for improving data locality on CC-NUMA compute servers, Technical Report CSL-TR-96-688, Computer System Laboratory, Stanford University, February 1996.
– reference: J. Tao, W. Karl, M. Schulz, Using simulation to understand the data layout of programs, in: Proceedings of the IASTED International Conference on Applied Simulation and Modelling (ASM 2001), Marbella, Spain, September 2001, pp. 349–354.
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  article-title: Thread migration and its applications in distributed shared memory systems
  publication-title: J. Syst. Softw.
  doi: 10.1016/S0164-1212(98)00008-9
– ident: 10.1016/S0167-739X(02)00183-8_BIB12
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SubjectTerms Data locality optimization
Hardware monitor
Page migration
Shared memory programming on NUMA
Title ARS: an adaptive runtime system for locality optimization
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