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of the Thesis Energy and Performance Evaluation of Lossless File Data Compression on Computer Systems by Rachita Kothiyal Master of Science in Computer ScienceStony Brook University 2009Data compression has been claimed to be an attractive solution to save energy consumption in high-end servers and data centers. However, there has not been a study to explore this. In this thesis, we present a comprehensive evaluation of energy consumption for various file compression techniques implemented in software. We apply various compression tools available on Linux to a variety of data files, and we try them on server, workstation and laptop class systems. We compare their energy and performance results against raw reads and writes. Our results reveal that software based data compression cannot be considered as a universal solution to reduce energy consumption. Various factors like the type of the data file, the compression tool being used, the read-to-write ratio of the workload, and the hardware configuration of the system impact the efficacy of this technique. We found that in some cases, compression can save as much as 33% energy and improve performance by 37.85%. However, in other cases we found that compression can increase energy consumption 7 times and deteriorate performance 4 fold.iii To my parents and my sisters, Ruchi and Rachna.

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of the ThesisOptimizing Energy and Performance for Server-Class File System Workloads by Priya Sehgal Master of Science in Computer ScienceStony Brook University 2010Recently, power has emerged as a critical factor in designing components of storage systems, especially for power-hungry data centers. While there is some research into power-aware storage stack components, there are no systematic studies evaluating each component's impact separately. Various factors like workloads, hardware configurations, and software configurations impact the performance and energy efficiency of the system. This thesis evaluates the file system's impact on energy consumption and performance. We studied several popular Linux file systems, with various mount and format options, using the FileBench workload generator to emulate four server workloads: Web, database, mail, and file server, on two different hardware configurations. The file system design, implementation, and available features have a significant effect on CPU/disk utilization, and hence on performance and power. We discovered that default file system options are often suboptimal, and even poor. In this thesis we show that a careful matching of expected workloads and hardware configuration to a single software configuration-the file system-can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times.iii To my parents and my brother and sister.

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