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AvA: Accelerated Virtualization of Accelerators

Authors: Hangchen Yu; Arthur Michener Peters; Amogh Akshintala; Christopher J. Rossbach;

AvA: Accelerated Virtualization of Accelerators

Abstract

Applications are migrating en masse to the cloud, while accelerators such as GPUs, TPUs, and FPGAs proliferate in the wake of Moore's Law. These trends are in conflict: cloud applications run on virtual platforms, but existing virtualization techniques have not provided production-ready solutions for accelerators. As a result, cloud providers expose accelerators by dedicating physical devices to individual guests. Multi-tenancy and consolidation are lost as a consequence. We present AvA, which addresses limitations of existing virtualization techniques with automated construction of hypervisor-managed virtual accelerator stacks. AvA combines a DSL for describing APIs and sharing policies, device-agnostic runtime components, and a compiler to generate accelerator-specific components such as guest libraries and API servers. AvA uses Hypervisor Interposed Remote Acceleration (HIRA), a new technique to enable hypervisor-enforcement of sharing policies from the specification. We use AvA to virtualize nine accelerators and eleven framework APIs, including six for which no virtualization support has been previously explored. AvA provides near-native performance and can enforce sharing policies that are not possible with current techniques, with orders of magnitude less developer effort than required for hand-built virtualization support.

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    29
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
bronze