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Christopher Healy
Researcher at Furman University
Publications - 35
Citations - 1525
Christopher Healy is an academic researcher from Furman University. The author has contributed to research in topics: Static timing analysis & Compiler. The author has an hindex of 17, co-authored 35 publications receiving 1492 citations. Previous affiliations of Christopher Healy include Florida State University.
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Journal ArticleDOI
Bounding pipeline and instruction cache performance
TL;DR: This paper describes an approach for bounding the worst and best case performance of large code segments on machines that exploit both pipelining and instruction caching and indicates that the timing analyzer efficiently produces tight predictions of best and best-case performance for pipelined and instruction cache.
Journal ArticleDOI
Where A Is Ordinary: The Evolution of American College and University Grading, 1940-2009.
TL;DR: In this paper, the authors show that college grades can influence a student's graduation prospects, academic motivation, postgraduate job choice, professional and graduate school selection, and access to loans and sc
Proceedings ArticleDOI
Integrating the timing analysis of pipelining and instruction caching
TL;DR: This paper describes an approach for bounding the worst-case performance of large code segments on machines that exploit both pipelining and instruction caching, and a graphical user interface is invoked that allows a user to request timing predictions on portions of the program.
Proceedings ArticleDOI
Timing analysis for data caches and set-associative caches
TL;DR: Results of incorporating instruction cache predictions within pipeline simulation show that timing predictions for set-associative caches remain just as tight as predictions for direct-mapped caches.
Journal ArticleDOI
Supporting Timing Analysis by Automatic Bounding of LoopIterations
TL;DR: Three complementary methods to support timing analysis by bounding the number of loop iterations are described and have been successfully integrated in an existing timing analyzer that predicts the performance for optimized code on a machine that exploits caching and pipelining.