Ginseng: Market-driven LLC allocation

Liran Funaro, Orna Agmon Ben-Yehuda, Assaf Schuster

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Cloud providers must dynamically allocate their physical resources to the right client to maximize the benefit that they can get out of given hardware. Cache Allocation Technology (CAT) makes it possible for the provider to allocate last level cache to virtual machines to prevent cache pollution. The provider can also allocate the cache to optimize client benefit. But how should it optimize client benefit, when it does not even know what the client plans to do? We present an auction-based mechanism that dynamically allocates cache while optimizing client benefit and improving hardware utilization. We evaluate our mechanism on benchmarks from the Phoronix Test Suite. Experimental results show that Ginseng for cache allocation improved clients' aggregated benefit by up to 42.8× compared with state-of-the-art static and dynamic algorithms.

Original languageEnglish
Title of host publicationProceedings of the 2016 USENIX Annual Technical Conference, USENIX ATC 2016
PublisherUSENIX Association
Number of pages14
ISBN (Electronic)9781931971300
StatePublished - 2016
Externally publishedYes
Event2016 USENIX Annual Technical Conference, USENIX ATC 2016 - Denver, United States
Duration: 22 Jun 201624 Jun 2016

Publication series

NameProceedings of the 2016 USENIX Annual Technical Conference, USENIX ATC 2016


Conference2016 USENIX Annual Technical Conference, USENIX ATC 2016
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2016 by The USENIX Association. All Rights Reserved.

ASJC Scopus subject areas

  • General Computer Science


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