Open Access. Powered by Scholars. Published by Universities.®

Computer and Systems Architecture Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 2 of 2

Full-Text Articles in Computer and Systems Architecture

Spatiotemporal Capacity Management For The Last Level Caches Of Chip Multiprocessors, Dongyuan Zhan Dec 2012

Spatiotemporal Capacity Management For The Last Level Caches Of Chip Multiprocessors, Dongyuan Zhan

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Judicious management of on-chip last-level caches (LLC) is critical to alleviating the memory wall of chip multiprocessors (CMP). Although there already exist many LLC management proposals, belonging to either the spatial or temporal dimension, they fail to capture and utilize the inherent interplays between the two dimensions in capacity management. Therefore, this dissertation is targeted at exploring and exploiting the spatiotemporal interactions in LLC capacity management to improve CMPs' performance. Based on this general idea, we address four specific research problems in the dissertation.

For the private LLC organization, prior-art proposals can improve the efficacy of inter-core cooperative caching at …


A Scalable Inline Cluster Deduplication Framework For Big Data Protection, Yinjin Fu, Hong Jiang, Nong Xiao May 2012

A Scalable Inline Cluster Deduplication Framework For Big Data Protection, Yinjin Fu, Hong Jiang, Nong Xiao

CSE Technical Reports

Cluster deduplication has become a widely deployed technology in data protection services for Big Data to satisfy the requirements of service level agreement (SLA). However, it remains a great challenge for cluster deduplica- tion to strike a sensible tradeoff between the conflicting goals of scalable dedu- plication throughput and high duplicate elimination ratio in cluster systems with low-end individual secondary storage nodes. We propose Σ-Dedupe, a scalable inline cluster deduplication framework, as a middleware deployable in cloud da- ta centers, to meet this challenge by exploiting data similarity and locality to op- timize cluster deduplication in inter-node and intra-node scenarios, …