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Run-time performance monitoring of hardware accelerators: POSTER

Published: 30 April 2019 Publication History

Abstract

In the era of Cyber Physical Systems, designers need to offer support for run-time adaptivity considering different constraints, including the internal status of the system. This work proposes a run-time monitoring approach for hardware accelerators, based on the Performance Application Programming Interface.

References

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L. Adhianto et al. 2010. HPCToolkit: Tools for performance analysis of optimized parallel programs. Concurrency and Computation: Practice and Experience 22, 6 (2010), 685--701.
[2]
Performance API. 2019. (2019). http://icl.utk.edu/papi/
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Reiner Hartenstein. 2001. Coarse grain reconfigurable architecture (embedded tutorial). In Cnf. of the Asia and South Pacific Design Automation.
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A. Knüpfer et al. 2008. The vampir performance analysis tool-set. Tools for High Performance Computing (2008), 139--155.
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D. Madroñal et al. 2018. Automatic Instrumentation of Dataflow Applications Using PAPI. In ACM International Conference on Computing Frontiers.
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M. Masin et al. 2017. Cross-layer design of reconfigurable cyber-physical systems. In Design, Automation Test in Europe Conference Exhibition.
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F. Palumbo et al. 2017. Power-Awarness in Coarse-Grained Reconfigurable Multi-Functional Architectures: a Dataflow Based Strategy. Journal of Signal Processing Systems 87, 1 (01 Apr 2017), 81--106.
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A. Rodríguez et al. 2018. FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo<sup>3</sup> Framework. Sensors 18, 6 (2018).
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Carlo Sau et al. 2015. Reconfigurable coprocessors synthesis in the MPEG-RVC domain. In Int. Conf. on ReConFigurable Computing and FPGAs.
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A. G. Schmidt et al. 2012. HwPMI: An Extensible Performance Monitoring Infrastructure for Improving Hardware Design and Productivity on FPGAs. Int. J. Reconfig. Comput. 2012, Article 2 (Jan. 2012), 1 pages.
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L. Suriano et al. 2018. A Unified Hardware/Software Monitoring Method for Reconfigurable Computing Architectures Using PAPI. In ReCoSoC'18.

Cited By

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  • (2021)A Composable Monitoring System for Heterogeneous Embedded PlatformsACM Transactions on Embedded Computing Systems10.1145/346164720:5(1-34)Online publication date: 9-Jul-2021
  • (2019)Hardware/Software Self-adaptation in CPS: The CERBERO Project ApproachEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-030-27562-4_30(416-428)Online publication date: 8-Aug-2019
  1. Run-time performance monitoring of hardware accelerators: POSTER

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    cover image ACM Conferences
    CF '19: Proceedings of the 16th ACM International Conference on Computing Frontiers
    April 2019
    414 pages
    ISBN:9781450366854
    DOI:10.1145/3310273
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 30 April 2019

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    Author Tags

    1. hw adaptivity
    2. hw monitoring
    3. hw reconfiguration

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    CF '19
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    CF '19: Computing Frontiers Conference
    April 30 - May 2, 2019
    Alghero, Italy

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    Overall Acceptance Rate 273 of 785 submissions, 35%

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    View all
    • (2021)A Composable Monitoring System for Heterogeneous Embedded PlatformsACM Transactions on Embedded Computing Systems10.1145/346164720:5(1-34)Online publication date: 9-Jul-2021
    • (2019)Hardware/Software Self-adaptation in CPS: The CERBERO Project ApproachEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-030-27562-4_30(416-428)Online publication date: 8-Aug-2019

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