Abstract
The task-based approach to software and parallelism is well-known and has been proposed as a potential candidate, named the silver model, for exascale software. This approach is not yet widely used in the large-scale multi-core parallel computing of complex systems of partial differential equations. After surveying task-based approaches we investigate how well the Uintah software and an extension named Wasatch fit in the task-based paradigm and how well they perform on large scale parallel computers. The conclusion is that these approaches show great promise for petascale but that considerable algorithmic challenges remain.
Chapter PDF
Similar content being viewed by others
References
Amarasinghe, S., Campbell, D., Carlson, W., Chien, A., Dally, W., Elnohazy, E., Hall, M., Harrison, R., Harrod, W., Hill, K., Hiller, J., Karp, S., Koelbel, C., Koester, D., Kogge, P., Levesque, J., Reed, D., Sarkar, V., Schreiber, R., Richards, M., Scarpelli, A., Shalf, J., Snavely, A., Sterling, T.: Exascale computing study: Software challenges in achieving exascale systems. Technical Report ECSS Report 101909, Georgia Institute of Technology (2009)
Atlas, S., Banerjee, S., Cummings, J.C., Hinker, P.J., Srikant, M., Reynders, J.V.W., Tholburn, M.: POOMA: A high-performance distributed simulation environment for scientific applications. In: Supercomputing 1995 Proceedings (December 1995)
Balay, S., Gropp, W.D., McInnes, L.C., Smith, B.F.: Efficient management of parallelism in object oriented numerical software libraries. In: Arge, E., Bruaset, A.M., Langtangen, H.P. (eds.) Modern Soft.Tools in Scien. Comput., pp. 163–202. Birkhäuser (1997)
Berger, M., Rigoutsos, I.: An algorithm for point clustering and grid generation. IEEE Trans. Systems Man Cybernet. 21(5), 1278–1286 (1991)
Berzins, M., Luitjens, J., Meng, Q., Harman, T., Wight, C.A., Peterson, J.R.: Uintah - a scalable framework for hazard analysis. In: TG 2010: Proceedings of the 2010 TeraGrid Conference. ACM, New York (2010)
Chandramowlishwaran, A., Knobe, K., Vuduc, R.: Performance evaluation of Concurrent Collections on high-performance multicore computing systems. In: Proc. IEEE Int’l. Parallel and Distributed Processing Symp (IPDPS), Atlanta, GA, USA (April 2010)
Falgout, R.D., Jones, J.E., Yangi, U.M.: The design and implementation of hypre, a library of parallel high performance preconditioners. In: Numerical Solution of Partial Differential Equations on Parallel Computers, pp. 267–294. Springer, Heidelberg (2006)
Bosilca, G., Bouteiller, A., Danalis, A., Faverge, M., Haidar, H., Herault, T., Kurzak, J., Langou, J., Lemariner, P., Ltaief, H., Luszczek, P., YarKhan, A., Dongarra, J.: Distibuted dense numerical linear algebra algorithms on massively parallel architectures: Dplasma. Technical report, Innovative Computing Laboratory, University of Tennessee (2010)
Guilkey, J.E., Harman, T.B., Banerjee, B.: An eulerian-lagrangian approach for simulating explosions of energetic devices. Computers and Structures 85, 660–674 (2007)
Spinti, J., Thornock, J., Eddings, E., Smith, P.J., Sarofim, A.: Heat transfer to objects in pool fires, in transport phenomena in fires. In: Transport Phenomena in Fires, Southampton, U.K. WIT Press (2008)
Kale, L.V., Bohm, E., Mendes, C.L., Wilmarth, T., Zheng, G.: Programming petascale applications with Charm++ and AMPI. Petascale Computing: Algorithms and Applications 1, 421–441 (2007)
Kashiwa, B.A.: A multifield model and method for fluid-structure interaction dynamics. Technical Report LA-UR-01-1136, Los Alamos National Laboratory, Los Alamos (2001)
Kurzak, J., Ltaief, H., Dongarra, J., Badia, R.: Scheduling dense linear algebra operations on multicore processors. Concurrency and Computation: Practice and Experience 22(1), 15–44 (2010)
Luitjens, J., Berzins, M.: Improving the performance of Uintah: A large-scale adaptive meshing computational framework. In: Proceedings of the 24th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2010 (2010)
Luitjens, J., Berzins, M.: Scalable parallel regridding algorithms for block-structured adaptive mesh renement. In: Concurrency And Computation: Practice And Experience (2011)
Luitjens, J., Berzins, M., Henderson, T.: Parallel space-filling curve generation through sorting: Research articles. Concurr. Comput.: Pract. Exper. 19(10), 1387–1402 (2007)
Martin, I., Tirado, F.: Relationships between efficiency and execution time of full multigrid methods on parallel computers. IEEE Transactions on Parallel and Distributed Systems 8(6), 562–573 (1997)
Meng, Q., Berzins, M., Schmidt, J.: Using hybrid parallelism to improve memory use in the Uintah framework. In: TG 2011: Proceedings of the 2011 TeraGrid Conference. ACM, New York (2011)
Meng, Q., Luitjens, J., Berzins, M.: Dynamic task scheduling for the Uintah framework. In: Proceedings of the 3rd IEEE Workshop on Many-Task Computing on Grids and Supercomputers, MTAGS 2010 (2010)
Notz, P.K., Pawlowski, R.P., Sutherland, J.C.: Graph-based software design for managing complexity and enabling concurrency in multiphysics pde software. ACM Transactions on Mathematical Software (submitted)
Parker, S.G.: A component-based architecture for parallel multi-physics pde simulation. Future Gener. Comput. Syst. 22(1), 204–216 (2006)
Parker, S.G., Guilkey, J., Harman, T.: A component-based parallel infrastructure for the simulation of fluid-structure interaction. Engineering with Computers 22, 277–292 (2006)
Parker, S.G., Guilkey, J.E., Harman, T.: A component-based parallel infrastructure for the simulation of fluid structure interaction. Eng. with Comput. 22(3), 277–292 (2006)
Sarkar, V.: Partitioning and Scheduling Parallel Programs for Multiprocessors. MIT Press, Cambridge (1989)
Sarkar, V., Skedzielewski, S., Miller, P.: An automatically partitioning compiler for sisal. In: Proceedings of the Conference on CONPAR 1988, pp. 376–383. Cambridge University Press, New York (1989)
Sinnen, O., Sousa, L.A., Frode, E.S.: Toward a realistic task scheduling model. IEEE Trans. Parallel Distrib. Syst. 17, 263–275 (2006)
Sulsky, D., Zhou, S., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer Physics Communications 87, 236–252 (1995)
Vajracharya, S., Karmesin, S., Beckman, P., Crotinger, J., Malony, A., Shende, S., Oldehoeft, R., Smith, S.: Smarts: Exploiting temporal locality and parallelism through vertical execution (1999)
Valiant, L.G.: Optimally universal parallel computers, pp. 17–20. Prentice Hall Press, Upper Saddle River (1989)
Sarkar, V., Harrod, W., Snavely, A.E.: Scidac review: Software challenges in extreme scale systems. Journal of Physics: Conference Series 180 012045 (2009)
Budimlic, Z., Burke, M., Cavé, V., Knobe, K., Lowney, G., Newton, R., Palsberg, J., Peixotto, D.M., Sarkar, V., Schlimbach, F., Tasirlar, S.: Concurrent collections. Scientific Programming 18(3-4), 203–217 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Berzins, M., Meng, Q., Schmidt, J., Sutherland, J.C. (2012). DAG-Based Software Frameworks for PDEs. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29737-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-29737-3_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29736-6
Online ISBN: 978-3-642-29737-3
eBook Packages: Computer ScienceComputer Science (R0)