Volume 13 Number 5 (May 2018)
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JCP 2018 Vol.13(5): 490-502 ISSN: 1796-203X
doi: 10.17706/jcp.13.5.490-502

A Case Study of Novice Programmers on Parallel Programming Models

Xuechao Li1, Po-Chou Shih2, Xueqian Li3, Cheryl Seals1
1Dept. of Computer Science, Auburn University, 345 W. Magnolia Ave, Auburn, Alabama, USA.
2Graduate Institute of Industrial and Business Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd, Taipei, Taiwan.
3Dept. of Civil Engineering, Auburn University, 238 Harbert Engineering Center, Auburn, Alabama, USA.

Abstract—High performance computing (HPC) languages have been developed over many years but the ability to write parallel program has not been fully studied based on the programmer effort subjects. In this paper for obtaining quantitative comparison results, we conducted an empirical experiment, which quantified four indices related to the programming productivity of CUDA and OpenACC: the achieved speedup, programmers’ workload on parallel solutions, effort per line of code and the dispersion on speedup. Twenty-eight students were recruited to finish two parallel problems: Machine Problem 3(MP3) and Machine Problem 4 (MP4) and the research data was collected by a WebCode website developed by ourselves. The statistical results indicated that (1) the speedup in OpenACC is 11.3x less than CUDA speedup; (2) the workload of developing OpenACC solutions is at least 2.3x less than CUDA ones; (3) the effort per line of code in OpenACC is not significantly less than CUDA; (4) and the OpenACC dispersion on speedup is significantly less than CUDA.

Index Terms—Development effort, programming productivity, empirical experiment, OpenACC, CUDA.


Cite: Xuechao Li, Po-Chou Shih, Xueqian Li, Cheryl Seals, "A Case Study of Novice Programmers on Parallel Programming Models," Journal of Computers vol. 13, no. 5, pp. 490-502, 2018.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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