A Gpu Implementation Of Inclusion-Based Points-To Analysis Essay

A GPU implementation of inclusion-based points-to analysis

Authors: Mario Mendez-LojoUniversity of Texas, Austin, TX, USA
Martin BurtscherTexas State University, San Marcos, TX, USA
Keshav PingaliUniversity of Texas, Austin, TX, USA
Published in:


 
· Proceeding
PPoPP '12 Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Pages 107-116

New Orleans, Louisiana, USA — February 25 - 29, 2012
ACMNew York, NY, USA ©2012
table of contents ISBN: 978-1-4503-1160-1 doi>10.1145/2145816.2145831
· Newsletter
ACM SIGPLAN Notices - PPOPP '12
Volume 47 Issue 8, August 2012
Pages 107-116
ACMNew York, NY, USA
table of contentsdoi>10.1145/2370036.2145831
2012 Article
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· Citation Count: 26
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algorithmscudagpugraph algorithmsinclusion-based points-to analysisirregular programslanguagesparallel programming languagesperformance

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Seminar on Program Analysis

ECS 289C (Programming Languages and Compilers)

Winter 2015

General Information

Instructor: Cindy Rubio-González
Time and Location:TR 1:40p-3:00p, 146 Robbins
Contact E-mail:crubio AT ucdavis DOT edu
Phone Number: (530) 752-7069
Office Hours:TR 5:00p-6:00p or by appointment
Office:Kemper Hall 3039
Credits:4 credits

Course Overview

This course will explore research in the area of programming languages, with particular emphasis on program analysis. Program analysis is the process of automatically analyzing the behavior of computer programs to discover facts. Topics include static analysis (dataflow analysis, model checking, type inference), dynamic analysis (software testing, automated debugging, automatic program repair), and hybrid approaches. We will cover a wide variety of application domains, and languages. This course is intended for graduate students interested in starting research in the area of programming languages, or graduate students whose ongoing research could benefit from program analysis.

Syllabus [PDF]
Preliminary Reading List [PDF]

Course Schedule

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