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Author Zhou, Yanqi ♦ Wentzlaff, David ♦ Hoffmann, Henry
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract Infrastructure as a Service (IaaS) Clouds have grown increasingly important. Recent architecture designs support IaaS providers through fine-grain configurability, allowing providers to orchestrate low-level resource usage. Little work, however, has been devoted to supporting IaaS customers who must determine how to use such fine-grain configurable resources to meet quality-of-service (QoS) requirements while minimizing cost. This is a difficult problem because the multiplicity of configurations creates a non-convex optimization space. In addition, this optimization space may change as customer applications enter and exit distinct processing phases. In this paper, we overcome these issues by proposing CASH: a fine-grain configurable architecture co-designed with a cost-optimizing runtime system. The hardware architecture enables configurability at the granularity of individual ALUs and L2 cache banks and provides unique interfaces to support low-overhead, dynamic configuration and monitoring. The runtime uses a combination of control theory and machine learning to configure the architecture such that QoS requirements are met and cost is minimized. Our results demonstrate that the combination of fine-grain configurability and non-convex optimization provides tremendous cost savings (70% savings) compared to coarse-grain heterogeneity and heuristic optimization. In addition, the system is able to customize configurations to particular applications, respond to application phases, and provide near optimal cost for QoS targets.
Description Affiliation: Princeton University (Zhou, Yanqi; Wentzlaff, David) || University of Chicago (Hoffmann, Henry)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1981-04-01
Publisher Place New York
Journal ACM SIGARCH Computer Architecture News (CARN)
Volume Number 44
Issue Number 3
Page Count 13
Starting Page 682
Ending Page 694


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Source: ACM Digital Library