CacheInspector

Author:

Song Weijia1,Delimitrou Christina1,Shen Zhiming2,Renesse Robbert Van1,Weatherspoon Hakim1,Benmohamed Lotfi3,Vaulx Frederic De3,Mahmoudi Charif4

Affiliation:

1. Cornell University, Ithaca, NY

2. Exotanium Inc., Ithaca, NY

3. National Institute of Standards and Technology, Gaithersburg, MD

4. Siemens Corporate Technology, Princeton, NJ

Abstract

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.

Funder

National Institute of Standards and Technology

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference74 articles.

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