The Message Passing Interface (MPI) is a software platform that can utilize the parallel capabilities of most multi-processors, making it useful for teaching students about parallel and distributed computing (PDC). MPI provides language bindings for Fortran and C/C++, but many university instructors lack expertise in these languages, preventing them from using MPI in their courses. OpenMPI is a free implementation of MPI that also provides Java bindings, allowing instructors who know Java but not C/C++ or Fortran to teach PDC. However, Java has a reputation as a “slow” language, so some say it is unsuitable for teaching PDC. This paper gives a head-to-head comparison of the performance of OpenMPI's Java and C bindings. Our study shows that by default, Java can be faster than C unless one takes special measures, and it exhibits similar speedup, efficiency, and scalability. We conclude that Java is a suitable language for teaching PDC.
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Teaching Parallel and Distributed Computing Concepts Using OpenMPI and Java
The ACM/IEEE CS 2013 curriculum recommendations state that every undergraduate CS major should learn about parallel and distributed computing (PDC). One way to accomplish this is to teach students about the Message Passing Interface (MPI), a platform that is commonly used on modern supercomputers and Beowulf clusters, but can also be used on a Network of Workstations (NoW), or a multicore laptop or desktop. MPI incorporates many PDC concepts and can serve as a platform for hands-on learning activities in which students must apply those concepts. The MPI standard defines language bindings for Fortran and C/C++, but many university instructors lack expertise in these languages, preventing them from using MPI in their courses. OpenMPI is a free implementation of the MPI standard that also provides Java bindings for MPI. This paper describes how to install OpenMPI with these Java bindings; to illustrate the use of these bindings, the paper also presents several patternlets—minimalist example programs—that show how to implement PDC design patterns using OpenMPI and Java. This provides a new means of introducing students to PDC concepts.
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- Award ID(s):
- 1822486
- NSF-PAR ID:
- 10353959
- Editor(s):
- Ghafoor, Sheikh; Prasad, Sushil K.
- Date Published:
- Journal Name:
- 3rd Workshop on Education for High Performance Computing (EduHiPC 2021), at 2021 IEEE 28th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)
- Page Range / eLocation ID:
- 4 to 11
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/HiPCW54834.2021.00008
