Strategies for preparing computer science students for the multicore world

Brown, Richard A.; Shoop, Elizabeth; Adams, Joel C.; Clifton, Curtis; Gardner, Mark K.; Haupt, Michael; Hinsbeeck, Peter

doi:10.1145/1971681.1971689

Cited by 38 publications

(14 citation statements)

References 56 publications

(41 reference statements)

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“…A 2010 ITiCSE working group explored the issue of integrating parallelism into computer science curricula in great detail, providing a range of references on potential content and approaches that have been tried [3]. Our approach to fork-join parallelism based on recursive algorithms and work/span has been long advocated by parallel-programming leaders such as Charles Leisersen and Guy Blelloch.…”

Section: Related Workmentioning

confidence: 99%

“…in undergraduate computer science curricula. However, as described in a recent exploration of the subject [3], there is not yet consensus on where in the curriculum to introduce these topics and what fundamental concepts are most important. In the near term, many institutions may find it equally unrealistic to, on the one hand, modify many courses so that multithreading pervades the curriculum or, on the other hand, add an entire required course.…”

Section: Introductionmentioning

confidence: 99%

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Introducing parallelism and concurrency in the data structures course

Grossman

Anderson

2012

Proceedings of the 43rd ACM Technical Symposium on Computer Science Education

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We report on our experience integrating a three-week introduction to multithreading in a required data structures course for second-year computer science majors. We emphasize a distinction between parallelism and concurrency that teaches students to use extra processors effectively and enforce mutual exclusion correctly. The material fits naturally in the data structures course by having the same mix of algorithms, programming, and asymptotic analysis as the conventional, single-threaded part of the course.Our department has used this unit for 1.5 years and will do so indefinitely. We report feedback from students, multiple instructors for the course, and students in a later course that uses threads. We developed a full set of course materials that have been adapted for use by instructors in various courses at five other institutions so far.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Introducing parallelism and concurrency in the data structures course

Grossman

Anderson

2012

Proceedings of the 43rd ACM Technical Symposium on Computer Science Education

View full text Add to dashboard Cite

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“…In [11] the authors advocate presenting parallel programming exercises whose results have broad appeal - [12,13] mention image processing and encryption as examples of domains that are well-suited.…”

Section: Related Workmentioning

confidence: 99%

Teaching parallelism with river trail

Sreeram

Herhut

Hudson

et al. 2012

Proceedings of the 2012 Workshop on Developing Competency in Parallelism: Techniques for Education and Training

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Parallel hardware is today's reality and parallel programming models exist for most mainstream languages. Surprisingly JavaScript, the mother tongue of the web, is still stuck in its sequential past. JavaScript's unique programming model, the web's safety and security requirements, and the expectations of its programmers for determinism have impeded parallelization until now.Parallel JavaScript (code named River Trail) is a set of JavaScript extensions and an API that provides safe, deterministic parallelism to web applications while fitting within the event-driven, security oriented world of JavaScript applications. River Trail allows programmers to utilize available hardware parallelism on client machines -from SIMD units to multiple cores, using high-level parallel programming patterns.In this paper we describe River Trail, show how it can be used to provide a gentle introduction to parallelism using our selfcontained hands-on tutorial. At the end of the tutorial the student will have mastered the basic concepts of parallel programming and use this knowledge to build a realistic parallel HTML5 web application in River Trail.

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“…CS Education research advocates the use of "hands-on experiential learning" [19] for teaching PDC concepts, while recommending a high degree of interactivity in the classroom [19,17]. In all cases, microclusters had a definite "cool" factor that encouraged student engagement and enthusiasm for PDC concepts.…”

Section: Strategies For Introducing Microclustersmentioning

confidence: 99%

Using Inexpensive Microclusters and Accessible Materials for Cost-Effective Parallel and Distributed Computing Education

Adams¹,

Matthews²,

Shoop³

et al. 2017

JOCSE

Self Cite

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With parallel and distributed computing (PDC) now in the core CS curriculum, CS educators are building new pedagogical tools to teach their students about this cutting-edge area of computing. In this paper, we present an innovative approach we call microclusters -personal, portable Beowulf clusters -that provide students with hands-on PDC learning experiences. We present several different microclusters, each built using a different combination of single board computers (SBCs) as its compute nodes, including various ODROID models, Nvidia's Jetson TK1, Adapteva's Parallella, and the Raspberry Pi. We explore different ways that CS educators are using these systems in their teaching, and describe specific courses in which CS educators have used microclusters. Finally, we present an overview of sources of free PDC pedagogical materials that can be used with microclusters.

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Strategies for preparing computer science students for the multicore world

Cited by 38 publications

References 56 publications

Introducing parallelism and concurrency in the data structures course

Introducing parallelism and concurrency in the data structures course

Teaching parallelism with river trail

Using Inexpensive Microclusters and Accessible Materials for Cost-Effective Parallel and Distributed Computing Education

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