Massive supercomputing coping with heterogeneity of modern accelerators

IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

Volumn , Issue , 2008, Pages

  Endo, Toshio ^a   Matsuoka, Satoshi ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATIONS; COMPUTER NETWORKS; DISTRIBUTED PARAMETER NETWORKS; SUPERCOMPUTERS;

CPU CORES; HETEROGENEOUS SYSTEMS; PARALLEL AND DISTRIBUTED PROCESSING;

BENCHMARKING;

EID: 51049096377     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPS.2008.4536251     Document Type: Conference Paper

References (18)

1. ClearSpeed Technology Inc. http://www.clearspeed.com/.
2. NVIDIA CUDA Homepage. http://developer.nvidia.com/cuda.
3. TOP500 supercomputer sites. http://www.top500.org/.
4. J. C. N. J. C. Lemuet, J. Sampson. The potential energy efficiency of vector acceleration. In Proceedings of IEEE/ACM SC06 Conference, 2006.
5. P. E. Crandall and M. J. Quinn. Block data decomposition for data-parallel programming on a heterogeneous workstation network. In Proceedings of IEEE International Symposium on High Performance Distributed Computing (HPDC), pages 42-49, 1993.
6. T. Endo, K. Kaneda, K. Taura, and A. Yonezawa. High performance LU factorization for non-dedicated clusters. In Proceedings of IEEE International Symposium on Cluster Computing and the Grid (CCGrid), pages 678-685, 2004.
7. D. P. et al. The design and implementation of a first-generation CELL processor. In Proceedings of IEEE International Solid-State Circuits Conference (ISSCC), pages 184-, 2005.
8. N. R. A. et al. An overview of the BlueGene/L supercomputer. In Proceedings of IEEE/ACM SC02 Conference, 2002.
9. J. F. A. L. M. K. F. Petrini, G. Fossum and M. Perrone. Multicore surprises: Lessons learned from optimizing sweep3d on the cell broadband engine. In Proceedings of IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2007.
10. K. Fatahalian, T. J. Knight, M. Houston, M. Erez, D. R. Horn, L. Leem, J. Y. Park, M. Ren, A. Aiken, W. J. Dally, and P. Hanrahan. Sequoia: Programming the memory hierarchy. In Proceedings of IEEE/ACM SC06 Conference, 2006.
11. N. Galoppo, N. K. Govindaraju, M. Henson, and D. Manocha. LU-GPU: Efficient algorithms for solving dense linear systems on graphics hardware. In Proceedings of IEEE/ACM SC05 Conference, 2005.
12. K. Goto. Goto BLAS. http://www.tacc.utexas.edu/resources/software/.
13. N. K. Govindaraju, S. Larsen, J. Gray, and D. Manocha. A memory model for scientific algorithms on graphics processors. In Proceedings of IEEE/ACM SC06 Conference, 2006.
14. C. Huang, G. Zheng, S. Kumar, and L. V. Kale. Performance evaluation of adaptive MPI. In Proceedings of ACM Symposium on Principles and Practice of Parallel Programming (PPoPP), pages 12-21, 2006.
15. Y. Kishimoto and S. Ichikawa. An execution-time estimation model for heterogeneous clusters. In Proceedings of IEEE International Heterogeneous Computing Workshop (HCW), 2004.
16. S. Ohshima, K. Kise, T. Katagiri, and T. Yuba. Parallel processing of matrix multiplication in a CPU and GPU heterogeneous environment. In 7th International Meeting on High Performance Computing for Computational Science (VECPAR'06), pages 41-50, July 2006.
17. A. Petitet, R. C. Whaley, J. Dongarra, and A. Cleary. HPL - a portable implementation of the high-performance Linpack benchmark for distributed-memory computers. http://www.netlib.org/benchmark/hpl/.
18. D. Tarditi, S. Puri, and J. Oglesby. Accelerator: Using data parallelism to program GPUs for general-purpose uses. In Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-XII), 2006.