242
M. Tsuji et.al.
9 Summary
In this chapter, we have presented the mSPMD programming model and programming environment, where several SPMD programs work together under the control
of a workflow program. YML, which is a development and execution environment
for scientific workflows, and its middleware OmniRPC, have been extended to
manage several SPMD tasks and programs. As well as MPI, XMP, a directivebased parallel programming language, has been supported to describe tasks. A task
generator has been developed to incorporate XMP programs into a workflow. Faulttolerant features, correctness check, and some numerical libraries’ implementations
in the mSPMD programming model have been presented.
References
1. C. Augonnet, S. Thibault, R. Namyst, P.-A. Wacrenier, StarPU: a unified platform for task
scheduling on heterogeneous multicore architectures. Concurr. Comput. Pract. Exp. 23, 187–
198 (2011). Euro-Par 2009
2. O. Delannoy, YML: A Scientific Workflow for High Performance Computing, PhD thesis,
University of Versailles Saint-Quentin (2006)
3. O. Delannoy, N. Emad, S. Petiton, Workflow global computing with YML, in The 7th
IEEE/ACM International Conference on Grid Computing (2006), pp. 25–32
4. O. Delannoy, S. Petiton, A peer to peer computing framework: design and performance
evaluation of YML, in 3rd International Workshop on Algorithms, Models and Tools for
Parallel Computing on Heterogeneous Networks (2004), pp. 362–369
5. T. Hilbrich, F. Hasel, M. Schulz, B.R. de Supinski, M.S. Muller, W.E. Nagel, Runtime MPI
collective checking with tree-based overlay networks, in Proceedings of the 20th European
MPI Users’ Group Meeting (EuroMPI 13) (ACM, Madrid, 2013), pp. 129–134
6. T. Hilbrich, J. Protze, M. Schulz, B.R. de Supinski, M.S. Muller, MPI runtime error
detection with MUST: advances in deadlock detection, in International Conference on High
Performance Computing, Networking, Storage and Analysis (SC12) (IEEE, Washington, DC,
2012)
7. T. Odajima, T. Boku, M. Sato, T. Hanawa, Y. Kodama, R. Namyst, S. Thibault, O. Aumage,
Adaptive task size control on high level programming for GPU/CPU work sharing, in
International Symposium on Advances of Distributed and Parallel Computing (ADPC 2013)
(2013), pp. 59–68
8. J. Protze, C. Terboven, M.S. Müller, S. Petiton, N. Emad, H. Murai, T. Boku, Runtime
correctness checking for emerging programming paradigms, in Proceedings of the First
International Workshop on Software Correctness for HPC Applications (2017), pp. 21–27
9. M. Sato, M. Hirano, Y. Tanaka, S. Sekiguchi, OmniRPC: a grid RPC facility for cluster and
global computing in OpenMP, in International Workshop on OpenMP Applications and Tools
(2001), pp. 130–136
10. D.C. Sorensen, Implicitly restarted Arnoldi/Lanczos methods for large scale eigenvalue
calculations, in Parallel Numerical Algorithms. ICASE/LaRC Interdisciplinary Series in
Science and Engineering Book Series (ICAS), vol. 4 (Springer, Dordrecht, 1997), pp. 119–
165
11. SuiteSparse Matrix Collection, https://sparse.tamu.edu/
12. The MUST Project, https://www.itc.rwth-aachen.de/must
M. Tsuji et.al.
9 Summary
In this chapter, we have presented the mSPMD programming model and programming environment, where several SPMD programs work together under the control
of a workflow program. YML, which is a development and execution environment
for scientific workflows, and its middleware OmniRPC, have been extended to
manage several SPMD tasks and programs. As well as MPI, XMP, a directivebased parallel programming language, has been supported to describe tasks. A task
generator has been developed to incorporate XMP programs into a workflow. Faulttolerant features, correctness check, and some numerical libraries’ implementations
in the mSPMD programming model have been presented.
References
1. C. Augonnet, S. Thibault, R. Namyst, P.-A. Wacrenier, StarPU: a unified platform for task
scheduling on heterogeneous multicore architectures. Concurr. Comput. Pract. Exp. 23, 187–
198 (2011). Euro-Par 2009
2. O. Delannoy, YML: A Scientific Workflow for High Performance Computing, PhD thesis,
University of Versailles Saint-Quentin (2006)
3. O. Delannoy, N. Emad, S. Petiton, Workflow global computing with YML, in The 7th
IEEE/ACM International Conference on Grid Computing (2006), pp. 25–32
4. O. Delannoy, S. Petiton, A peer to peer computing framework: design and performance
evaluation of YML, in 3rd International Workshop on Algorithms, Models and Tools for
Parallel Computing on Heterogeneous Networks (2004), pp. 362–369
5. T. Hilbrich, F. Hasel, M. Schulz, B.R. de Supinski, M.S. Muller, W.E. Nagel, Runtime MPI
collective checking with tree-based overlay networks, in Proceedings of the 20th European
MPI Users’ Group Meeting (EuroMPI 13) (ACM, Madrid, 2013), pp. 129–134
6. T. Hilbrich, J. Protze, M. Schulz, B.R. de Supinski, M.S. Muller, MPI runtime error
detection with MUST: advances in deadlock detection, in International Conference on High
Performance Computing, Networking, Storage and Analysis (SC12) (IEEE, Washington, DC,
2012)
7. T. Odajima, T. Boku, M. Sato, T. Hanawa, Y. Kodama, R. Namyst, S. Thibault, O. Aumage,
Adaptive task size control on high level programming for GPU/CPU work sharing, in
International Symposium on Advances of Distributed and Parallel Computing (ADPC 2013)
(2013), pp. 59–68
8. J. Protze, C. Terboven, M.S. Müller, S. Petiton, N. Emad, H. Murai, T. Boku, Runtime
correctness checking for emerging programming paradigms, in Proceedings of the First
International Workshop on Software Correctness for HPC Applications (2017), pp. 21–27
9. M. Sato, M. Hirano, Y. Tanaka, S. Sekiguchi, OmniRPC: a grid RPC facility for cluster and
global computing in OpenMP, in International Workshop on OpenMP Applications and Tools
(2001), pp. 130–136
10. D.C. Sorensen, Implicitly restarted Arnoldi/Lanczos methods for large scale eigenvalue
calculations, in Parallel Numerical Algorithms. ICASE/LaRC Interdisciplinary Series in
Science and Engineering Book Series (ICAS), vol. 4 (Springer, Dordrecht, 1997), pp. 119–
165
11. SuiteSparse Matrix Collection, https://sparse.tamu.edu/
12. The MUST Project, https://www.itc.rwth-aachen.de/must