Generating parallel applications for distributed memory systems using aspects, components, and patterns

ABSTRACT

Developing and debugging parallel programs particularly for distributed memory architectures is still a difficult task. The most popular approach to developing parallel programs for distributed memory architectures requires adding explicit message passing calls into existing sequential programs for data distribution, coordination, and communication. This approach creates separate source tree for sequential code and parallel code as well as further branches based on the specific set of message passing primitives used (point-to-point communication vs. one-sided communication). Aspect oriented programming provides an option to separate programming concerns and weave code into applications instead of directly modifying the original program. This paper described an effort to use Aspect Oriented Programming (specifically AspectC++), components and patterns for data distribution and message passing to develop parallel programs without making any changes to existing sequential program. This technique is used to generate a suite of parallel matrix multiplication algorithms as well as several simple parallel algorithms without making any changes to the sequential code. Performance results obtained indicate that the desired functionality is achieved without compromising performance.

REFERENCES

• 1: AspectC Homepage. http://www.aspectc.net.
• 2: AspectC++ Homepage. http://www.aspectc.org.
• 3: Tarek El-Ghazawi , William Carlson , Thomas Sterling , Katherine Yelick, UPC: Distributed Shared-Memory Programming, Wiley-Interscience, 2003
• 4: Grama, A., Gupta, A., Karypis, G., Kumar, V., Introduction to Parallel Computing, 2nd Edition, Addison Wesley, 2003.
• 5: A Flexible Class of Parallel Matrix Multiplication Algorithms, Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium, p.110, March 30-April 03, 1998
• 6: Bruno Harbulot , John R. Gurd, Using AspectJ to separate concerns in parallel scientific Java code, Proceedings of the 3rd international conference on Aspect-oriented software development, p.122-131, March 22-24, 2004, Lancaster, UK [doi>10.1145/976270.976286]
• 7: High Performance Fortran Forum, High Performance Fortran Language Specification, Scientific Programming 2(1-2), pp. 1--170, 1993.
• 8: Kiczales, G., Lamping, J., Mendhekar, A., Maeda, C., Videira Lopes, C., Loingtier, J. and Irwin, J., Aspect-Oriented Programming, European Conference on Object-Oriented Programming (ECOOP), LNCS 1241, Springer-Verlag, Jyväskylä, Finland, June 1997, pp. 220--242.
• 9: Li, J., Skjellum, A., Falgout, R. D., A poly-algorithm for parallel dense matrix multiplication on two-dimensional process grid topologies. Concurrency: Practice and Experience, 9(5), pp. 345--389, 1997.
• 10: Message Passing Interface Forum, "MP12: A Message-Passing Interface Standard," International Journal of Supercomputer Applications and High Performance Computing, Special Issue, 12(1/2), pp. 1--299, 1998.
• 11: Sobral, J. Incrementally Developing Parallel Applications with AspectJ, 20th IEEE International Parallel & Distributed Processing Symposium (IPDPS'06), Greece, Rhodes, April 2006, IEEE Computer Society, 2006.
• 12: V. S. Sunderam, PVM: a framework for parallel distributed computing, Concurrency: Practice and Experience, v.2 n.4, p.315-339, Dec. 1990 [doi>10.1002/cpe.4330020404]
• 13: V. S. Sunderam, PVM: a framework for parallel distributed computing, Concurrency: Practice and Experience, v.2 n.4, p.315-339, Dec. 1990 [doi>10.1002/cpe.4330020404]
• 14: Kai Tan , Duane Szafron , Jonathan Schaeffer , John Anvik , Steve MacDonald, Using generative design patterns to generate parallel code for a distributed memory environment, Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming, June 11-13, 2003, San Diego, California, USA
• 15: TOP500 Supercomputer Sites. http://www.top500.org.

INDEX TERMS

Primary Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.3 Language Constructs and Features
          Subjects: Abstract data types

Additional Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.3 Language Constructs and Features
          Subjects: Patterns; Concurrent programming structures; Polymorphism

Keywords:
aspect oriented programming, parallel programming, patterns