Abstract
With the rapid advance of computing technologies, it becomes more and more common to construct high-performance computing environments with heterogeneous commodity computers. Previous loop scheduling schemes were not designed for this kind of environments. Therefore, better loop scheduling schemes are needed to further increase the performance of the emerging heterogeneous PC cluster environments. In this paper, we propose a new heuristic for the performance-based approach to partition loop iterations according to the performance weighting of cluster/grid nodes. In particular, a new parameter is proposed to consider HPCC benchmark results as part of performance estimation. A heterogeneous cluster and grid were built to verify the proposed approach, and three kinds of application program were implemented for execution on cluster testbed. Experimental results show that the proposed approach performs better than the previous schemes on heterogeneous computing environments.
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References
Baker M, Buyya R (2002) Cluster computing: the commodity supercomputer. Softw Pract Exp 29(6):551–575, 1999
Beaumont O, Casanova H, Legrand A, Robert Y, Yang Y (2005) Scheduling divisible loads on star and tree networks: results and open problems. IEEE Trans Parall Distrib Syst 16:207–218
Bennett BH, Davis E, Kunau T, Wren W (2000) Beowulf parallel processing for dynamic load-balancing. Proc IEEE Aerosp Conf 4:389–395
Bohn CA, Lamont GB (2002) Load balancing for heterogeneous clusters of PCs. Future Gener Comput Syst 18:389–400
Challenge Benchmark HPC. http://icl.cs.utk.edu/hpcc/
Cheng K-W, Yang C-T, Lai C-L, Chang S-C (2004) A parallel loop self-scheduling on grid computing environments. In: Proceedings of the 2004 IEEE international symposium on parallel architectures, algorithms and networks, KH, China, May 2004, pp 409–414
Chronopoulos AT, Andonie R, Benche M, Grosu D (2001) A class of loop self-scheduling for heterogeneous clusters. In: Proceedings of the 2001 IEEE international conference on cluster computing, pp 282–291
Hummel SF, Schonberg E, Flynn LE (1992) Factoring: a method scheme for scheduling parallel loops. Commun ACM 35:90–101
Introduction to the Mandelbrot Set, http://www.ddewey.net/mandelbrot/
Li H, Tandri S, Stumm M, Sevcik KC (1993) Locality and loop scheduling on NUMA multiprocessors. In: Proceedings of the 1993 international conference on parallel processing, vol II, pp 140–147
Polychronopoulos CD, Kuck D (1987) Guided self-scheduling: a practical scheduling scheme for parallel supercomputers. IEEE Trans Comput 36(12):1425–1439
Post E, Goosen HA (2001) Evaluation of the parallel performance of a heterogeneous system. In: Proceedings of 5th international conference and exhibition on high-performance computing in the Asia-Pacific region (HPC Asia 2001)
Shih W-C, Yang C-T, Tseng S-S (2005) A performance-based parallel loop self-scheduling on grid environments. In: Network and parallel computing: IFIP international conference, NPC 2005. Lecture notes in computer science, vol 3779. Springer, Berlin, pp 48–55
Shih W-C, Yang C-T, Tseng S-S (2005) A hybrid parallel loop scheduling scheme on grid environments. In: Grid and cooperative computing: 4th international conference, GCC 2005. Lecture notes in computer science, vol 3795. Springer, Berlin, pp 370–381
Shih W-C, Yang C-T, Tseng S-S (2005) A hybrid parallel loop scheduling scheme on heterogeneous PC clusters. In: Proceedings of the 6th international conference on parallel and distributed computing, applications and technologies (PDCAT 2005), December 5–8, 2005, pp 56–58
Shih W-C, Yang C-T, Tseng S-S (2006) A performance-based approach to dynamic workload distribution for master–slave applications on grid environments. In: GPC 2006. Lecture notes in computer science, vol 3947. Springer, Berlin, pp 73–82
Shih W-C, Yang C-T, Tseng S-S (2007) A performance-based parallel loop scheduling on grid environments. J Supercomput 41(3):247–267
Sterling T, Bell G, Kowalik JS (2002) Beowulf cluster computing with Linux. MIT Press, Cambridge
Tang P, Yew PC (1986) Processor self-scheduling for multiple-nested parallel loops. In: Proceedings of the 1986 international conference on parallel processing, pp 528–535
The Scalable Computing Laboratory (SCL), http://www.scl.ameslab.gov/
Tzen TH, Ni LM (1993) Trapezoid self-scheduling: A practical scheduling scheme for parallel compilers. IEEE Trans Parallel Distrib Syst 4:87–98
Yang C-T, Chang S-C (2004) A parallel loop self-scheduling on extremely heterogeneous PC clusters. J Inf Sci Eng 20(2):263–273
Yang C-T, Cheng K-W, Li K-C (2004) An efficient parallel loop self-scheduling on grid environments. In: Jin H, Gao G, Xu Z (eds) NPC’2004 IFIP international conference on network and parallel computing. Lecture notes in computer science, vol 3222. Springer, Heidelberg, pp 92–100
Yang C-T, Cheng K-W, Li K-C (2005) An enhanced parallel loop self-scheduling scheme for cluster environments. J Supercomput 34(3):315–335
Yang C-T, Cheng K-W, Shih W-C (2007) On development of an efficient parallel loop self-scheduling for grid computing environments. Parallel Comput 33(7–8):467–487
Yang C-T, Shih W-C, Tseng S-S (2007) Dynamic partitioning of loop iterations on heterogeneous PC clusters. J Supercomput 44(1):1–23
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Yang, CT., Shih, WC. & Cheng, LH. Performance-based dynamic loop scheduling in heterogeneous computing environments. J Supercomput 59, 414–442 (2012). https://doi.org/10.1007/s11227-010-0443-x
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DOI: https://doi.org/10.1007/s11227-010-0443-x