Abstract
The theory of bulk-synchronous parallel computing has produced a large number of attractive algorithms, which are provably optimal in some sense, but typically require that the aggregate random access memory (RAM) of the processors be sufficient to hold the entire data set of the parallel problem instance. In this work we investigate the performance of parallel algorithms for extremely large problem instances relative to the available RAM. We describe a system, Parallel External Memory System (PEMS), which allows existing parallel programs designed for a large number of processors without disks to be adapted easily to smaller, realistic numbers of processors, each with its own disk system. Our experiments with PEMS show that this approach is practical and promising and the run times scale predictable with the number of processors and with the problem size.
This work was partially supported by the National Sciences and Engineering Research Council of Canada (NSERC) and by the High Performance Computing Virtual Laboratory (HPCVL).
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References
Dehne, F.K.H.A., Dittrich, W., Hutchinson, D.A., Maheshwari, A.: Bulk synchronous parallel algorithms for the external memory model. Theory Comput. Syst. 35(6), 567–597 (2002)
Hutchinson, D.A.: Parallel Algorithms in External Memory. PhD thesis, School of Computer Science, Carleton University (1999)
Vitter, J.S., Shriver, E.A.M.: Algorithms for parallel memory, I: Two-level memories. Algorithmica 12(2–3), 110–147 (1994)
Crauser, M.: LEDA-SM: Extending LEDA to secondary memory. In: International, W.A.E. (ed.) WAE: International Workshop on Algorithm Engineering. LNCS (1999)
Dementiev, R., Kettner, L., Sanders, P.: STXXL: Standard template library for XXL data sets. In: Brodal, G.S., Leonardi, S. (eds.) ESA 2005. LNCS, vol. 3669, pp. 640–651. Springer, Heidelberg (2005)
Gustedt, J.: Towards realistic implementations of external memory algorithms using a coarse grained paradigm. In: Kumar, V., Gavrilova, M., Tan, C.J.K., L’Ecuyer, P. (eds.) ICCSA 2003. LNCS, vol. 2668, pp. 269–278. Springer, Heidelberg (2003)
Valiant, L.G.: A bridging model for parallel computation. Communications of the ACM 33(8), 103–111 (1990)
Open MPI, http://www.open-mpi.org/
GNU Pth - The GNU Portable Threads, http://www.gnu.org/software/pth/
Bader, D.A., Helman, D.R., JáJá, J.: Practical parallel algorithms for personalized communication and integer sorting. ACM JEA 1, 3 (1996)
Shi, H., Schaeffer, J.: Parallel sorting by regular sampling. Journal of Parallel and Distributed Computing 14, 361–372 (1992)
Nikseresht, M.R.: A parallel external memory system. Master’s thesis, School of Computer Science, Carleton University (2007)
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Nikseresht, M.R., Hutchinson, D.A., Maheshwari, A. (2007). Experiments with a Parallel External Memory System. In: Aluru, S., Parashar, M., Badrinath, R., Prasanna, V.K. (eds) High Performance Computing – HiPC 2007. HiPC 2007. Lecture Notes in Computer Science, vol 4873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77220-0_10
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DOI: https://doi.org/10.1007/978-3-540-77220-0_10
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