NDLI: Lossy Compression for Worst-Case Execution Time Analysis of PLRU Caches

Content Provider	ACM Digital Library
Author	Griffin, David Davis, Robert I. Burns, Alan Lesage, Benjamin
Abstract	This paper outlines how Lossy Compression, a branch of Information Theory relating to the compact representation of data while retaining important information, can be applied to the Worst Case Execution Time analysis problem. In particular, we show that by applying lossy compression to the data structures involved in the collecting semantics of a given component, for example a PLRU cache, a useful analysis can be derived. While such an analysis could be found via other means, the application of Lossy Compression provides a formal method and eases the process of discovering the analysis. Further, as the compression and its application are formally specified, such an analysis can be made correct-by-construction rather than relying on an after-the-fact proof.
Starting Page	203
Ending Page	212
Page Count	10
File Format	PDF
ISBN	9781450327275
DOI	10.1145/2659787.2659807
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-10-08
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Lossy Compression for Worst-Case Execution Time Analysis of PLRU Caches