research-article

Abstract machine models and proxy architectures for exascale computing

Authors:

A. F. Rodrigues,

N. J. WrightAuthors Info & Claims

Co-HPC '14: Proceedings of the 1st International Workshop on Hardware-Software Co-Design for High Performance Computing

Pages 25 - 32

https://doi.org/10.1109/Co-HPC.2014.4

Published: 16 November 2014 Publication History

Abstract

To achieve exascale computing, fundamental hardware architectures must change. This will significantly impact scientific applications that run on current high performance computing (HPC) systems, many of which codify years of scientific domain knowledge and refinements for contemporary computer systems. To adapt to exascale architectures, developers must be able to reason about new hardware and determine what programming models and algorithms will provide the best blend of performance and energy efficiency in the future. An abstract machine model is designed to expose to the application developers and system software only the aspects of the machine that are important or relevant to performance and code structure. These models are intended as communication aids between application developers and hardware architects during the co-design process. A proxy architecture is a parameterized version of an abstract machine model, with parameters added to elucidate potential speeds and capacities of key hardware components. These more detailed architectural models enable discussion among the developers of analytic models and simulators and computer hardware architects and they allow for application performance analysis, system software development, and hardware optimization opportunities. In this paper, we present a set of abstract machine models and show how they might be used to help software developers prepare for exascale. We then apply parameters to one of these models to demonstrate how a proxy architecture can enable a more concrete exploration of how well application codes map onto future architectures.

References

[1]

R. F. Barrett, S. D. Hammond, C. T. Vaughan, D. W. Doerfler, M. A. Heroux, J. P. Luitjens, and D. Roweth. Navigating an Evolutionary Fast Path to Exascale. In High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:, pages 355--365. IEEE, 2012.

Digital Library

[2]

Michael Bauer, Sean Treichler, Elliott Slaughter, and Alex Aiken. Legion: Expressing locality and independence with logical regions.

[3]

R. Brightwell and K. D. Underwood. An Analysis of NIC Resource Usage for Offloading MPI. In Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International, pages 183--, April 2004.

[4]

Byn Choi et al. Denovo: Rethinking the memory hierarchy for disciplined parallelism. In Proceedings of the 2011 International Conference on Parallel Architectures and Compilation Techniques, PACT '11, pages 155--166, Washington, DC, USA, 2011. IEEE Computer Society.

Digital Library

[5]

Jack Dongarra et al. The International Exascale Software Project Roadmap. IJHPCA, 25(1):3--60, 2011.

Digital Library

[6]

JEDEC. Wide I/O Single Data Rate. JESC 229, JEDEC, December 2011. http://www.jedec.org/standards-documents/docs/jesd229.

[7]

JEDEC. High Bandwidth Memory (HBM) DRAM. JESC 235, JEDEC, October 2013. http://www.jedec.org/standards-documents/docs/jesd235.

[8]

JEDEC. Solid state memories committee. Web, September 2014. http://www.jedec.org/committees/jc-42ex-2.

[9]

Hartmut Kaiser. High performance parallex (hpx). Web, November 2011. http://stellar.cct.lsu.edu/publications/.

[10]

Himanshu Kaul, Mark Anders, Steven Hsu, Amit Agarwal, Ram Krishnamurthy, and Shekhar Borkar. Near-threshold voltage (ntv) design: opportunities and challenges. In DAC, pages 1153--1158, 2012.

Digital Library

[11]

S. Kaxiras and G. Keramidas. Sarc coherence: Scaling directory cache coherence in performance and power. Micro, IEEE, 30(5):54--65, Sept 2010.

Digital Library

[12]

Martha Kim. Scaling Theory and Machine Abstractions. http://www.cs.columbia.edu/~martha/courses/4130/au13/pdfs/scaling-theory.pdf, Sept 2013.

[13]

Peter M. Kogge and John Shalf. Exascale computing trends: Adjusting to the "new normal"' for computer architecture. Computing in Science and Engineering, 15(6):16--26, 2013.

Digital Library

[14]

Mark Lapedus. What's next for memory. Web, August 2014. http://semiengineering.com/whats-next-for-memory/.

[15]

Robert Lucas AND et. al. Top Ten Exascale Research Challenges, DOE ASCAC Subcommittee Report, February 2014.

[16]

A. Ros, B. Cuesta, M. E. Gomez, A. Robles, and J. Duato. Cache miss characterization in hierarchical large-scale cache-coherent systems. In Parallel and Distributed Processing with Applications (ISPA), 2012 IEEE 10th International Symposium on, pages 691--696, July 2012.

Digital Library

[17]

M. Schuchhardt, A. Das, N. Hardavellas, G. Memik, and A. Choudhary. The impact of dynamic directories on multicore interconnects. Computer, 46(10):32--39, October 2013.

Digital Library

[18]

John Shalf, Sudip S. Dosanjh, and John Morrison. Exascale computing technology challenges. In VECPAR, pages 1--25, 2010.

Digital Library

[19]

Micron Technology. Hybrid Memory Cube Specification, 2014.

[20]

K. D. Underwood, K. S. Hemmert, A. Rodrigues, R. Murphy, and R. Brightwell. A Hardware Acceleration Unit for MPI Queue Processing. In Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International, pages 96b--96b, April 2005.

Digital Library

[21]

Leslie G. Valiant. A bridging model for parallel computation. Commun. ACM, 33(8):103--111, August 1990.

Digital Library

[22]

Yi Xu, Yu Du, Youtao Zhang, and Jun Yang. A composite and scalable cache coherence protocol for large scale cmps. In Proceedings of the International Conference on Supercomputing, ICS '11, pages 285--294, New York, NY, USA, 2011. ACM.

Digital Library

Cited By

Keyes D(2021)The Arab world prepares the exascale workforceCommunications of the ACM10.1145/344773764:4(82-87)Online publication date: 22-Mar-2021
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Farooqi MIzbassarov DMuradoğlu MUnat D(2019)Communication analysis and optimization of 3D front tracking method for multiphase flow simulationsInternational Journal of High Performance Computing Applications10.1177/109434201769442633:1(67-80)Online publication date: 1-Jan-2019
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Ghane MChandrasekaran SCheung M(2019)GeckoProceedings of the 10th International Workshop on Programming Models and Applications for Multicores and Manycores10.1145/3303084.3309489(21-30)Online publication date: 17-Feb-2019
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Published In

cover image ACM Conferences

Co-HPC '14: Proceedings of the 1st International Workshop on Hardware-Software Co-Design for High Performance Computing

November 2014

82 pages

ISBN:9781479975648

Sponsors

SIGHPC: ACM Special Interest Group on High Performance Computing, Special Interest Group on High Performance Computing
IEEE: IEEE Computer Society Technical Committee on Design Automation
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture

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IEEE Press

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Published: 16 November 2014

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SC '14

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SC '14: International Conference for High Performance Computing, Networking, Storage and Analysis

November 16 - 21, 2014

Louisiana, New Orleans

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Overall Acceptance Rate 7 of 13 submissions, 54%

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Cited By

Keyes D(2021)The Arab world prepares the exascale workforceCommunications of the ACM10.1145/344773764:4(82-87)Online publication date: 22-Mar-2021
https://dl.acm.org/doi/10.1145/3447737
Farooqi MIzbassarov DMuradoğlu MUnat D(2019)Communication analysis and optimization of 3D front tracking method for multiphase flow simulationsInternational Journal of High Performance Computing Applications10.1177/109434201769442633:1(67-80)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1177/1094342017694426
Ghane MChandrasekaran SCheung M(2019)GeckoProceedings of the 10th International Workshop on Programming Models and Applications for Multicores and Manycores10.1145/3303084.3309489(21-30)Online publication date: 17-Feb-2019
https://dl.acm.org/doi/10.1145/3303084.3309489
Rizzi FMorris KSargsyan KMycek PSafta CLe Maître OKnio ODebusschere B(2018)Partial differential equations preconditioner resilient to soft and hard faultsInternational Journal of High Performance Computing Applications10.1177/109434201668497532:5(658-673)Online publication date: 1-Sep-2018
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Searles RChandrasekaran SJoubert WHernandez O(2018)Abstractions and Directives for Adapting Wavefront Algorithms to Future ArchitecturesProceedings of the Platform for Advanced Scientific Computing Conference10.1145/3218176.3218228(1-10)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3218176.3218228
Qasem AAji ARodgers GReddi VSmith ATang L(2017)Characterizing data organization effects on heterogeneous memory architecturesProceedings of the 2017 International Symposium on Code Generation and Optimization10.5555/3049832.3049850(160-170)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3049832.3049850
Yan YBrightwell RSun X(2017)Principles of Memory-Centric Programming for High Performance ComputingProceedings of the Workshop on Memory Centric Programming for HPC10.1145/3145617.3158212(2-6)Online publication date: 12-Nov-2017
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Mhembere DZheng DPriebe CVogelstein JBurns RHuang HWeissman JIamnitchi AIosup A(2017)knorProceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3078597.3078607(67-78)Online publication date: 26-Jun-2017
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Zheng DMhembere DLyzinski VVogelstein JPriebe CBurns R(2017)Semi-External Memory Sparse Matrix Multiplication for Billion-Node GraphsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2016.261879128:5(1470-1483)Online publication date: 1-May-2017
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Blattner TKeyrouz WBhattacharyya SHalem MBrady M(2017)A Hybrid Task Graph Scheduler for High Performance Image Processing WorkflowsJournal of Signal Processing Systems10.1007/s11265-017-1262-689:3(457-467)Online publication date: 1-Dec-2017
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