Parallel programming with pictures is a Snap
For decades, computing speeds seemingly doubled every 24 months by increasing the processor clock speed, thus giving software a “free ride” to better performance. This free ride, however, effectively ended by the mid-2000s. With clock speeds having plateaued and computational horsepower instead incr...
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| Vydáno v: | Journal of parallel and distributed computing Ročník 105; s. 150 - 162 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Inc
01.07.2017
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| ISSN: | 0743-7315, 1096-0848 |
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| Abstract | For decades, computing speeds seemingly doubled every 24 months by increasing the processor clock speed, thus giving software a “free ride” to better performance. This free ride, however, effectively ended by the mid-2000s. With clock speeds having plateaued and computational horsepower instead increasing due to increasing the number of cores per processor, the vision for parallel computing, which started more than 40 years ago, is a revolution that has now (ubiquitously) arrived. In addition to traditional supercomputing clusters, parallel computing with multiple cores can be found in desktops, laptops, and even mobile smartphones.
This ubiquitous parallelism in hardware presents a major challenge: the difficulty in easily extracting parallel performance via current software abstractions. Consequently, this paper presents an approach that reduces the learning curve to parallel programming by introducing such concepts into a visual (but currently sequential) programming language called Snap!, which was inspired by MIT’s Scratch project. Furthermore, our proposed visual abstractions can automatically generate parallel code for the end user to run in parallel on a variety of platforms from personal computing devices to supercomputers. Ultimately, this work seeks to increase parallel programming literacy so that users, whether novice or experienced, may leverage a world of ubiquitous parallelism to enhance productivity in all walks of life, including the sciences, engineering, commerce, and liberal arts.
•Introduction of explicit parallel-programming constructs into a picture-programming environment.•Block-based programming abstractions to reduce the learning curve to parallel programming.•Automated generation of OpenMP code from our parallel picture-programming environment. |
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| AbstractList | For decades, computing speeds seemingly doubled every 24 months by increasing the processor clock speed, thus giving software a “free ride” to better performance. This free ride, however, effectively ended by the mid-2000s. With clock speeds having plateaued and computational horsepower instead increasing due to increasing the number of cores per processor, the vision for parallel computing, which started more than 40 years ago, is a revolution that has now (ubiquitously) arrived. In addition to traditional supercomputing clusters, parallel computing with multiple cores can be found in desktops, laptops, and even mobile smartphones.
This ubiquitous parallelism in hardware presents a major challenge: the difficulty in easily extracting parallel performance via current software abstractions. Consequently, this paper presents an approach that reduces the learning curve to parallel programming by introducing such concepts into a visual (but currently sequential) programming language called Snap!, which was inspired by MIT’s Scratch project. Furthermore, our proposed visual abstractions can automatically generate parallel code for the end user to run in parallel on a variety of platforms from personal computing devices to supercomputers. Ultimately, this work seeks to increase parallel programming literacy so that users, whether novice or experienced, may leverage a world of ubiquitous parallelism to enhance productivity in all walks of life, including the sciences, engineering, commerce, and liberal arts.
•Introduction of explicit parallel-programming constructs into a picture-programming environment.•Block-based programming abstractions to reduce the learning curve to parallel programming.•Automated generation of OpenMP code from our parallel picture-programming environment. |
| Author | Feng, Wu-chun Feng, Annette Gardner, Mark |
| Author_xml | – sequence: 1 givenname: Annette surname: Feng fullname: Feng, Annette email: afeng@vt.edu organization: Department of Computer Science, Virginia Tech, Blacksburg, VA, USA – sequence: 2 givenname: Mark surname: Gardner fullname: Gardner, Mark email: mkg@vt.edu organization: Department of Computer Science, Virginia Tech, Blacksburg, VA, USA – sequence: 3 givenname: Wu-chun surname: Feng fullname: Feng, Wu-chun email: wfeng@vt.edu organization: Department of Computer Science, Virginia Tech, Blacksburg, VA, USA |
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| Cites_doi | 10.1145/1953163.1953336 10.1145/1327452.1327492 10.1145/1592761.1592779 |
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| References_xml | – reference: The College Board, College Board and NSF Expand Partnership to Bring Computer Science Classes to High Schools Across the U.S. (June 2015). URL – reference: J. Dean, S. Ghemawat, Mapreduce: Simplified data processing on large clusters, Communications of the ACM - 50th Anniversary Issue: 1958–2008 51, 2008, pp. 107–113. – reference: W3C, Web Workers, w3c working draft 24 september 2015. URL – reference: (Checked 2016-12-13) (Dec 2012). – volume: 52 start-page: 60 year: 2009 end-page: 67 ident: br000060 article-title: Scratch: programming for all publication-title: Commun. ACM – reference: . – volume: 2 start-page: 126 year: 2013 end-page: 131 ident: br000010 article-title: The analysis of visual parallel programming languages publication-title: Adv. Comput. Sci.: Int. J. – reference: The College Board, College Board Officially Launches New AP Computer Science Principles Course to Increase Student Engagement in Computing (Dec 2014). URL – year: 1996 ident: br000015 article-title: Visual programming and parallel computing, Tech. Rep – year: 2013 ident: br000070 article-title: Operating System Concepts, ninth ed. – reference: Apache Software Foundation, Hadoop. URL – start-page: 662 year: 2012 ident: br000025 article-title: Snap!:(build your own blocks) publication-title: Proceedings of the 43rd ACM Technical Symposium on Computer Science Education – reference: E. Joseph, A. Snell, C. Willard, (July 2004). URL – reference: L. Meadows, T. Mattson, A hands-on introduction to openmp (November 2008). – reference: S.K. Prasad, A. Chtchelkanova, F. Dehne, M. Gouda, A. Gupta, J. Jaja, K. Kant, A.L. Salle, R. LeBlanc, A. Lumsdaine, D. Padua, M. Parashar, V. Prasanna, Y. Robert, A. Rosenberg, S. Sahni, B. Shirazi, A. Sussman, C. Weems, J. Wu, Nsf/ieee-tcpp curriculum initiative on parallel and distributed computing - core topics for undergraduates, version i, – reference: B. Harvey, J. Monig, Snap! reference manual. URL – year: 2003 ident: br000040 article-title: Taxonomy for visual parallel programming languages, Tech. Rep – reference: National Instruments, LabVIEW System Design Software. URL – reference: A. Savitzky, S. Mayr, Parallel.js. URL – ident: 10.1016/j.jpdc.2017.01.018_br000045 – year: 2013 ident: 10.1016/j.jpdc.2017.01.018_br000070 – ident: 10.1016/j.jpdc.2017.01.018_br000055 doi: 10.1145/1953163.1953336 – ident: 10.1016/j.jpdc.2017.01.018_br000075 – ident: 10.1016/j.jpdc.2017.01.018_br000020 doi: 10.1145/1327452.1327492 – ident: 10.1016/j.jpdc.2017.01.018_br000030 – ident: 10.1016/j.jpdc.2017.01.018_br000035 – ident: 10.1016/j.jpdc.2017.01.018_br000050 – volume: 52 start-page: 60 issue: 11 year: 2009 ident: 10.1016/j.jpdc.2017.01.018_br000060 article-title: Scratch: programming for all publication-title: Commun. ACM doi: 10.1145/1592761.1592779 – start-page: 662 year: 2012 ident: 10.1016/j.jpdc.2017.01.018_br000025 article-title: Snap!:(build your own blocks) – year: 2003 ident: 10.1016/j.jpdc.2017.01.018_br000040 – volume: 2 start-page: 126 issue: 4 year: 2013 ident: 10.1016/j.jpdc.2017.01.018_br000010 article-title: The analysis of visual parallel programming languages publication-title: Adv. Comput. Sci.: Int. J. – ident: 10.1016/j.jpdc.2017.01.018_br000005 – year: 1996 ident: 10.1016/j.jpdc.2017.01.018_br000015 – ident: 10.1016/j.jpdc.2017.01.018_br000085 – ident: 10.1016/j.jpdc.2017.01.018_br000065 – ident: 10.1016/j.jpdc.2017.01.018_br000080 |
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| SubjectTerms | Block-based programming Computer science education Explicit parallel computing Languages for PDC and HPC Parallel computational patterns Pedagogical tools Programming environments Visual programming |
| Title | Parallel programming with pictures is a Snap |
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