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Architecting an autograder for parallel code

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Susan MehringerAuthors Info & Claims

XSEDE '14: Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment

Article No.: 68, Pages 1 - 8

https://doi.org/10.1145/2616498.2616571

Published: 13 July 2014 Publication History

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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.

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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.

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Ruth BHott JStone JYuen TShoop LRebelsky SPrather J(2025)Auto-grading in Computing Education: Perceptions and UseProceedings of the 56th ACM Technical Symposium on Computer Science Education V. 110.1145/3641554.3701900(1008-1014)Online publication date: 12-Feb-2025
https://dl.acm.org/doi/10.1145/3641554.3701900
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
https://doi.org/10.1007/978-3-031-27534-0_4

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Architecting an autograder for parallel code

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Published In

XSEDE '14: Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment

July 2014

445 pages

ISBN:9781450328937

DOI:10.1145/2616498

General Chair:
Scott Lathrop
National Center for Supercomputing Applications
,
Program Chair:
Jay Alameda
National Center for Supercomputing Applications

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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NSF: National Science Foundation
Drexel University
Indiana University: Indiana University

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Association for Computing Machinery

New York, NY, United States

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Published: 13 July 2014

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XSEDE '14

XSEDE '14: Annual Conference of the Extreme Science and Engineering Discovery Environment

July 13 - 18, 2014

GA, Atlanta, USA

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XSEDE '14 Paper Acceptance Rate 80 of 120 submissions, 67%;

Overall Acceptance Rate 129 of 190 submissions, 68%

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Ruth BHott JStone JYuen TShoop LRebelsky SPrather J(2025)Auto-grading in Computing Education: Perceptions and UseProceedings of the 56th ACM Technical Symposium on Computer Science Education V. 110.1145/3641554.3701900(1008-1014)Online publication date: 12-Feb-2025
https://dl.acm.org/doi/10.1145/3641554.3701900
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
https://doi.org/10.1007/978-3-031-27534-0_4

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Pedagogy and tools for teaching parallel computing at the sophomore undergraduate level

Cognitive, metacognitive and motivational perspectives on preflection in self-regulated online learning

Understanding the Effect of In-Video Prompting on Learners and Instructors

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