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aFabric: Towards a Holistic View for Managing Hardware Accelerators in the Cloud

Published: 11 December 2020 Publication History
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  • Abstract

    As hardware accelerators are widely used in the cloud to reduce response time, it is impending to orchestrate and unify heterogeneous accelerators. In this paper, we describe an operating system paradigm for heterogeneous accelerators in the cloud and introduce our sketch design of an operating system, aFabric, using P4 language as the programming language for offloaded accelerator programs. Finally, we elaborate on the evaluation plan as the guideline of concrete design and implementation of aFabric in the future.

    References

    [1]
    AWS. Amazon ec2 f1 instances. https://tinyurl.com/y6cp3zeq, 2020.
    [2]
    P. Bosshart, G. Gibb, H.-S. Kim, G. Varghese, N. McKeown, M. Izzard, F. Mujica, and M. Horowitz. Forwarding metamorphosis: Fast programmable match-action processing in hardware for sdn. SIGCOMM '13, page 99--110. ACM, 2013.
    [3]
    Y. Zha and J. Li. Virtualizing fpgas in the cloud. In ASPLOS 2020, pages 845--858.

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    1. aFabric: Towards a Holistic View for Managing Hardware Accelerators in the Cloud

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          cover image ACM Conferences
          CoNEXT'20: Proceedings of the Student Workshop
          December 2020
          35 pages
          ISBN:9781450381833
          DOI:10.1145/3426746
          Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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          Publication History

          Published: 11 December 2020

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          Author Tags

          1. Cloud accelerators
          2. Heterogeneous hardware
          3. Operating system

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          Overall Acceptance Rate 198 of 789 submissions, 25%

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