2019Unpublished venueRequires access

Activity Based Approach for Teaching Parallel Computing: An Indian Experience

P. Chitra, Sheikh Ghafoor

Open publisher page 9 citations

Abstract

Due to the rapid growth in the multicore and GPU based computing devices, the need to teach parallel computing in CS/CE curriculum has become almost mandatory nowadays. A course on Parallel Computing Systems (PCS) has been designed to provide an understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. An activity based learning approach was adopted for teaching the course and several parallel programming paradigms and technologies such OpenMP, MPI, and CUDA have been covered. This course was offered as a required course to graduate students. This paper describes the implementation of the course at Thiagarajar College of Engineering. Evaluation of the implementation of the course reveals that for students who have not been exposed to parallel and distributed computing, i) activity based learning results in better knowledge gain compared to the traditional approach, ii) learning OpenMP was much easier than MPI or CUDA, iii) some Parallel and Distributed Computing (PDC) concepts such as false sharing were harder to grasp compared to basic concepts, and iv) it is essential to introduce parallel computing in the undergraduate curriculum.

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What this paper is about

Due to the rapid growth in the multicore and GPU based computing devices, the need to teach parallel computing in CS/CE curriculum has become almost mandatory nowadays. A course on Parallel Computing Systems (PCS) has been designed to provide an understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. An activity based learning approach was adopted for teaching the course and several parallel programming paradigms and technologies such OpenMP, MPI, and CUDA have been covered. This course was offered as a required course to graduate students. This paper describes the implementation of the course at Thiagarajar College of Engineering. Evaluation of the implementation of the course reveals that for students who have not been exposed to parallel and distributed computing, i) activity based learning results in better knowledge gain compared to the traditional approach, ii) learning OpenMP was much easier than MPI or CUDA, iii) some Parallel and Distributed Computing (PDC) concepts such as false sharing were harder to grasp compared to basic concepts, and iv) it is essential to introduce parallel computing in the undergraduate curriculum.

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Available abstract

Due to the rapid growth in the multicore and GPU based computing devices, the need to teach parallel computing in CS/CE curriculum has become almost mandatory nowadays. A course on Parallel Computing Systems (PCS) has been designed to provide an understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. An activity based learning approach was adopted for teaching the course and several parallel programming paradigms and technologies such OpenMP, MPI, and CUDA have been covered. This course was offered as a required course to graduate students. This paper describes the implementation of the course at Thiagarajar College of Engineering. Evaluation of the implementation of the course reveals that for students who have not been exposed to parallel and distributed computing, i) activity based learning results in better knowledge gain compared to the traditional approach, ii) learning OpenMP was much easier than MPI or CUDA, iii) some Parallel and Distributed Computing (PDC) concepts such as false sharing were harder to grasp compared to basic concepts, and iv) it is essential to introduce parallel computing in the undergraduate curriculum.

Key concepts: Computer science, CUDA, Multi-core processor, GRASP, Parallel computing, Curriculum, Computer architecture, Software engineering

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