On improving the performance of multi-threaded CUDA applications with concurrent kernel execution by kernel reordering

Symposium on Application Accelerators in High-Performance Computing

Volumn , Issue , 2012, Pages 74-83

  Wende, Florian ^a   Cordes, Frank ^b   Steinke, Thomas ^a  

^a ZUSE INSTITUTE BERLIN   (Germany)

^b GETLIG and TAR ^*  (Germany)

Author keywords

Concurrent kernel execution; CUDA; GP GPU; Multi threaded applications

Indexed keywords

CONCURRENT KERNEL EXECUTION; CUDA; GP-GPU; GRAPHICS PROCESSING UNITS; MASSIVE PARALLELISM; MULTI-THREADED APPLICATION; MULTI-THREADED PROGRAMS; MULTITHREADED; NANODROPLET; NUMERICAL COMPUTATIONS; PERFORMANCE IMPROVEMENTS; PROBLEM SIZE; REAL-WORLD APPLICATION; SINGLE-THREADED; SMALL MOLECULES; VIABLE SOLUTIONS;

COMPUTER GRAPHICS;

PROGRAM PROCESSORS;

EID: 84870690907     PISSN: 21665133     EISSN: 2166515X     Source Type: Conference Proceeding    
DOI: 10.1109/SAAHPC.2012.12     Document Type: Conference Paper

References (23)

1. R. Spurzem, P. Berczik, I. Berentzen, K. Nitadori, T. Hamada, G. M. Martinez, A. Kugel, R. M̈anner, J. Fiestas, R. Banerjee, and R. Klessen, "Astrophysical particle simulations with large custom GPU clusters on three continents, " Computer Science - R&D, vol. 26, no. 3-4, pp. 145-151, 2011.
2. R. Spurzem, P. Berczik, K. Nitadori, G. M. Martinez, A. Kugel, R. M̈anner, I. Berentzen, R. Klessen, and R. Banerjee, "Astrophysical Particle Simulations with Custom GPU Clusters, " in CIT. IEEE Computer Society, 2010, pp. 1189- 1195.
3. C. J. Fluke, D. G. Barnes, B. R. Barsdell, and A. H. Hassan, "Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters, " Publ.Astron.Soc.Austral., vol. 28, pp. 15-27, 2011.
4. Y. Liu, B. Schmidt, and D. L. Maskell, "CUDASW++2.0: enhanced Smith-Waterman protein database search on CUDAenabled GPUs based on SIMT and virtualized SIMD abstractions, " BMC Research Notes, vol. 3, p. 93, 2010.
5. W. Liu, B. Schmidt, Y. Liu, G. Voss, and W. M̈uller-Wittig, "Mapping of BLASTP Algorithm onto GPU Clusters, " in ICPADS. IEEE, 2011, pp. 236-243.
6. W. Liu, B. Schmidt, and W. M̈uller-Wittig, "CUDA-BLASTP: Accelerating BLASTP on CUDA-Enabled Graphics Hardware, " IEEE/ACM Trans. Comput. Biology Bioinform., vol. 8, no. 6, pp. 1678-1684, 2011.
7. J. E. Stone, D. J. Hardy, B. Isralewitz, and K. Schulten, "GPU algorithms for molecular modeling, " in Scientific Computing with Multicore and Accelerators, J. Dongarra, D. A. Bader, and J. Kurzak, Eds. Chapman & Hall/CRC Press, 2011, ch. 16, pp. 351-371.
8. J. E. Stone, J. C. Phillips, P. L. Freddolino, D. J. Hardy, L. G. Trabuco, and K. Schulten, "Accelerating molecular modeling applications with graphics processors, " Journal of Computational Chemistry, vol. 28, pp. 2618-264, 2007.
9. P. Eastman and V. Pande, "OpenMM: A Hardware- Independent Framework for Molecular Simulations, " Computing in Science and Engg., vol. 12, no. 4, pp. 34-39, Jul. 2010. [Online]. Available: http://dx.doi.org/10.1109/MCSE. 2010.27.
10. N. Luehr, I. S. Ufimtsev, and T. J. Martinez, "Dynamic Precision for Electron Repulsion Integral Evaluation on Graphical Processing Units (GPUs), " Journal of Chemical Theory and Computation, vol. 7, pp. 949-954, 2011.
11. I. S. Ufimtsev and T. J. Martinez, "Quantum Chemistry on Graphical Processing Units. 3. Analytical Energy Gradients and First Principles Molecular Dynamics, " Journal of Chemical Theory and Computation, vol. 5, pp. 2619-2628, 2009.
12. J. Beisheim, "Speed Up Simulations with a GPU, " ANSYS, Inc., Tech. Rep., 2010.
13. NVIDIA, NVIDIA's next generation CUDA Compute Architecture: Fermi (White paper v1.1), 2009.
14. NVIDIA CUDA C programming guide, v4.0, 2011.
15. L. Wang, M. Huang, and T. El-Ghazawi, "Exploiting Concurrent Kernel Execution on Graphic Processing Units, " in Proceedings of The 2011 International Conference on High Performance Computing & Simulation (HPCS 2011), Istanbul, Turkey, July 4-8 2011, pp. 24-32.
16. M. Guevara, C. Gregg, K. Hazelwood, and K. Skadron, "Enabling Task Parallelism in the CUDA Scheduler, " in Workshop on Programming Models for Emerging Architectures, ser. PMEA, Raleigh, NC, September 2009, pp. 69-76.
17. L. Wang, M. Huang, V. K. Narayana, and T. El- Ghazawi, "Scaling scientific applications on clusters of hybrid multicore/GPU nodes, " in Proceedings of the 8th ACM International Conference on Computing Frontiers, ser. CF '11. New York, NY, USA: ACM, 2011, pp. 6:1-6:10. [Online]. Available: http://doi.acm.org/10.1145/2016604.2016612.
18. L. Wang, M. Huang, and T. El-Ghazawi, "Towards efficient GPU sharing on multicore processors, " in Proceedings of the second international workshop on Performance modeling, benchmarking and simulation of high performance computing systems, ser. PMBS '11. New York, NY, USA: ACM, 2011, pp. 23-24. [Online]. Available: http://doi.acm.org/10.1145/2088457.2088473.
19. J. C. Phillips, J. E. Stone, and K. Schulten, "Adapting a message-driven parallel application to GPU-accelerated clusters, " in Proceedings of the 2008 ACM/IEEE conference on Supercomputing, ser. SC '08. Piscataway, NJ, USA: IEEE Press, 2008, pp. 8:1-8:9. [Online]. Available: http://dl.acm.org/citation.cfm?id=1413370.1413379.
20. NVIDIA, NVIDIA's next generation CUDA Compute Architecture: Kepler GK110 (White paper v1.0), 2012.
21. F. Haack and S. R̈oblitz and O. Scharkoi and B. Schmidt and M. Weber, "Adaptive Spectral Clustering for Conformation Analysis, " in AIP Conference Proceedings, vol. 1281, no. 1, 2010, pp. 1585-1588, http://link.aip.org/link/doi/10.1063/1.3498116.
22. T. A. Halgren, "Merck molecular force field. I-V. Basis, form, scope, parameterization, and performance of MMFF94, " J. of Comp. Chem., vol. 17, no. 5-6, pp. 490-641, 1996.
23. B. Hess, C. Kutzner, D. van der Spoel, and E. Lindahl, "GROMACS 4: Algorithms for Highly Efficient, Load- Balanced, and Scalable Molecular Simulation, " Journal of Chemical Theory and Computation, vol. 4, no. 3, pp. 435-447, 2008. [Online]. Available: http://pubs.acs.org/doi/abs/10.1021/ ct700301q.