Cited By
View all- Freiberger F(2023)Model Checking Concurrent Programs for Autograding in pseuCo BookFormal Methods Teaching10.1007/978-3-031-27534-0_4(51-65)Online publication date: 23-Feb-2023
Architecting an autograder for parallel code
Authors: 
Razvan Carbunescu, Aditya Devarakonda, 
James Demmel, 
Steven Gordon, Jay Alameda, Susan MehringerAuthors Info & Claims
Razvan Carbunescu, Aditya Devarakonda, James Demmel, Steven Gordon, Jay Alameda, Susan MehringerAuthors Info & ClaimsArticle No.: 68, Pages 1 - 8
Abstract
As parallel computing grows and becomes an essential part of computer science, tools must be developed to help grade assignments for large courses, especially with the prevalence of Massive Open Online Courses (MOOCs) increasing in recent years. This paper describes some of the general challenges related to building an autograder for parallel code with general suggestions and sample design decisions covering presented assignments. The paper explores the results and experiences from using these autograders to enable the XSEDE 2013 and 2014 Parallel Computing Course using resources from SDSC-Trestles, TACC-Stampede and PSC-Blacklight.
References
[1]
Autograding codes. https://www.eecs.berkeley.edu/~carazvan/XSEDE2014/grading.html.
[2]
Cornell virtual workshop. https://www.cac.cornell.edu/VW/.
[3]
Coursera. https://www.coursera.org/.
[4]
edX. https://www.edx.org/.
[5]
Heterogenous Parallel Programming. https://www.coursera.org/course/hetero.
[6]
MIT Open Courseware. http://ocw.mit.edu/courses/.
[7]
Moodle. https://moodle.org/.
[8]
Piazza. https://www.piazza.com/.
[9]
Udacity. https://www.udacity.com/.
[10]
Steven I. Gordon, Jay Alameda, James Demmel, Razvan Carbunescu, and Susan Mehringer. Providing a supported online course on parallel computing. In Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery, XSEDE '13, pages 60:1--60:4, New York, NY, USA, 2013. ACM.
[11]
Dorsa Sadigh, Sanjit A. Seshia, and Mona Gupta. Automating exercise generation: A step towards meeting the MOOC challenge for embedded systems. In Proceedings of the Workshop on Embedded and Cyber-Physical Systems Education, WESE '12, pages 2:1--2:8, New York, NY, USA, 2013. ACM.
[12]
Saul Schleimer, Daniel S Wilkerson, and Alex Aiken. Winnowing: Local algorithms for document fingerprinting. In Proceedings of the 2003 ACM SIGMOD international conference on Management of data, pages 76--85. ACM, 2003.
Index Terms
- Architecting an autograder for parallel code
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July 2014
445 pages
Copyright © 2014 ACM.
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In-Cooperation
- NSF: National Science Foundation
- Drexel University
- Indiana University: Indiana University
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 July 2014
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- Research-article
- Research
- Refereed limited
Conference
XSEDE '14
XSEDE '14: Annual Conference of the Extreme Science and Engineering Discovery Environment
July 13 - 18, 2014
GA, Atlanta, USA
Acceptance Rates
XSEDE '14 Paper Acceptance Rate 80 of 120 submissions, 67%;
Overall Acceptance Rate 129 of 190 submissions, 68%
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View all- Freiberger F(2023)Model Checking Concurrent Programs for Autograding in pseuCo BookFormal Methods Teaching10.1007/978-3-031-27534-0_4(51-65)Online publication date: 23-Feb-2023
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