Specialization tools and techniques for systematic optimization of system software

  • Authors:

  • Dylan McNamee;Jonathan Walpole;Calton Pu;Crispin Cowan;Charles Krasic;Ashvin Goel;Perry Wagle;Charles Consel;Gilles Muller;Renauld Marlet

  • Affiliations:

  • Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, 200000 NW Walker Road, Beaverton, OR;University of Rennes/IRISA;University of Rennes/IRISA;University of Rennes/IRISA

  • Venue:
  • ACM Transactions on Computer Systems (TOCS)
  • Year:
  • 2001

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Abstract

Specialization has been recognized as a powerful technique for optimizing operating systems. However, specialization has not been broadly applied beyond the research community because current techniques based on manual specialization, are time-consuming and error-prone. The goal of the work described in this paper is to help operating system tuners perform specialization more easily. We have built a specialization toolkit that assists the major tasks of specializing operating systems. We demonstrate the effectiveness of the toolkit by applying it to three diverse operating system components. We show that using tools to assist specialization enables significant performance optimizations without error-prone manual modifications. Our experience with the toolkit suggests new ways of designing systems that combine high performance and clean structure.