학술논문

PCASA: Probabilistic control-adjusted Selective Allocation for shared caches
Document Type
Conference
Source
2012 Design, Automation & Test in Europe Conference & Exhibition (DATE) Design, Automation & Test in Europe Conference & Exhibition (DATE), 2012. :473-478 Mar, 2012
Subject
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Resource management
Probabilistic logic
Monitoring
Art
Quality of service
Radiation detectors
Benchmark testing
Language
ISSN
1530-1591
1558-1101
Abstract
Chip Multi-Processors (CMPs) are designed with an increasing number of cores to enable multiple and potentially heterogeneous applications to run simultaneously on the same system. However, this results in increasing pressure on shared resources, such as shared caches. With multiple processor cores sharing the same caches, high-priority applications may end up contending with low-priority applications for cache space and suffer significant performance slow-down, hence affecting the Quality of Service (QoS). In datacenters, Service Level Agreements (SLAs) impose a reserved amount of computing resources and specific cache space per cloud customer. Thus, to meet SLAs, a deterministic capacity management solution is required to control the occupancy of all applications. In this paper, we propose a novel QoS architecture, based on Probabilistic Selective Allocation (PSA), for priority-aware caches. Further, we show that applying a control-theoretic approach (Proportional Integral controller) to dynamically adjust PSA provides accurate and fine-grained capacity management.