CacheInspector: Reverse Engineering Cache Resources in Public Clouds


연구 분야: Analysis



학회: ACM Transactions on Architecture and Code Optimization (TACO), Volume 18, Issue 3


초록

Infrastructure-as-a-Service cloud providers sell virtual machines that are only specified in terms of number of CPU cores, amount of memory, and I/O throughput. Performance-critical aspects such as cache sizes and memory latency are missing or reported in ways that make them hard to compare across cloud providers. It is difficult for users to adapt their application’s behavior to the available resources. In this work, we aim to increase the visibility that cloud users have into shared resources on public clouds. Specifically, we present CacheInspector, a lightweight runtime that determines the performance and allocated capacity of shared caches on multi-tenant public clouds. We validate CacheInspector’s accuracy in a controlled environment, and use it to study the characteristics and variability of cache resources in the cloud, across time, instances, availability regions, and cloud providers. We show that CacheInspector’s output allows cloud users to tailor their application’s behavior, including their output quality, to avoid suboptimal performance when resources are scarce.


Author Profile
Weijia Song

Cornell University Ithaca NY

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Christina Delimitrou

Cornell University Ithaca NY

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Zhiming Shen

Exotanium Inc. Ithaca NY

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📄 논문 정보

발행 연도 2021년
인용수 4
출판 국가 Andorra
사이트 ACM
좋아요 수 0

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