Exploiting capabilities of many core platforms in reservoir simulation

Society of Petroleum Engineers - SPE Reservoir Simulation Symposium 2011

Volumn 1, Issue , 2011, Pages 264-275

  Klie, Hector ^a   Sudan, Hari ^a   Li, Ruipeng ^b   Saad, Yousef ^b  

^a ConocoPhillips Company ^*  (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL ARITHMETIC; LINEAR SYSTEMS; PETROLEUM RESERVOIR ENGINEERING; PETROLEUM RESERVOIRS; SIMULATION PLATFORM;

ALGEBRAIC MULTIGRIDS; COMPOSITIONAL SIMULATIONS; COMPUTATIONAL EXPERIMENT; DEGREE OF NON-LINEARITY; FLOATING POINT OPERATIONS; LARGE SPARSE LINEAR SYSTEMS; MANY-CORE ARCHITECTURE; NUMERICAL COMPUTATIONS;

COMPUTER ARCHITECTURE;

EID: 79957916357     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2118/141265-ms     Document Type: Conference Paper

References (32)

1. F. Abrahamn and W. Celes. Distributed Visualization of Complex Black-Oil Reservoir Models. Eurographics Symposium on Parallel Graphics and Visualization, Braga, Portugal, 2009.
2. M. M. Baskaran and R. Bordawekar. Optimizing Sparse Matrix-Vector Multiplication on GPUs. Technical report, IBM Research, 2009.
3. N. Bell and M. Garland. Implementing Sparse Matrix-Vector Multiplication on Throughput-Oriented Processors. In SC '09: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis. Page 1-11. New York, NY, USA, 2009. ACM.
4. L. Buatois, G. Caumon, B. Levy. Concurrent number cruncher: A GPU Implementation of a General Sparse Linear solver. International Journal of Parallel, Emergent and Distributed Systems, 24: 205-223, 2009.
5. A. Bydal. GPU-Accelerated Simulation of Flow Through a Porous Medium. Master Thesis, Faculty of Engineering and Science, University of Agder, Grimstad, Norway, May, 2009.
6. D. Chen and S. Toledo. Vaidya's Preconditioners: Implementation and Experimental Study, Electron. Trans. Numer. Anal. 16: 30-49, 2003. (Pubitemid 38816934)
7. M. A. Christie and M.J. Blunt. Tenth SPE Comparative Solution Project: A Comparison of Upscaling Techniques. SPE Reservoir Simulation Symposium, SPE paper N. 72469, Houston, Feb. 11-14, 2001.
8. D. Tromeur-Dervout and Y. Vassilevski. Choice of Initial Guess in Iterative Solution of Series of Systems Arising in Fluid Flow Simulations. J. Comput. Phys., 219, 210-227, 2006.
9. B. Deschizeaux and J-Y. Blanc. Imaging Earth's Subsurface Using CUDA. GPU Gems 3, Chapter 38, H. Nguyen editor, NVIDIA Corporation, 831-850, 2008.
10. A. H. Dogru, L.S.K. Fung, U. Middya, T.M. Al-Shaalan, J.A. Pita, K. Hemanth, Kumar, H.J. Su, J.C.T. Tan, H. Hoy, W.T. Dreiman, W.A. Hahn, R.Al-Harbi, A. Al-Youbi, N.M. Al-Zamel. M.Mezghani, T. Al-Mani. A Next Generation Parallel Reservoir Simulator for Giant Reservoirs. SPE Reservoir Simulation Symposium, SPE paper N. 119272, The Woodlands, TX, Feb, 2009.
11. J. Dongarra and V. Eijkhout. Self-adapting Numerical Software and Automatic Tuning of Heuristics. In Proceedings of the International Conference on Computer Science, Melbourne, Australia, June 2-4, 2003.
12. J. Frank and C. Vuik. On The Construction of Deflation-Based Preconditioners. SlAM J. SCi. Comput. 23(2): 442-462, 2001.
13. M. Garland. Sparse Matrix Computations on Manycore GPU's. Proceedings of the 45th ACM/IEEE Annual Design Automation Conference. ACM, 2-6, 2008.
14. G. Karypis and V. Kumar. A Parallel Algorithm ofor Multilevel Graph Partitioning and Sparse Matrix Ordering. Journal of Parallel and Distributed Computing, 48: 71-95, 1998. (Pubitemid 128347295)
15. H. Klie. Parallel Sparsified Solvers for Reservoir Simulation. 12th European Conference on the Mathematics of Oil Recovery (ECMOR XII), Oxford, UK, Sept 6-9, 2010.
16. H. Klie, M.F. Wheeler, T. Clees and K. Stuben. Towards a New Generation of Physics-Driven Solvers for Black-Oil and Compositional Flow Simulation. SPE Reservoir Simulation Symposium, SPE paper N. 118752, The Woodlands, TX, Feb. 2-4, 2009.
17. H. Klie, M.F.Wheeler, T. Clees and K. Stuben. Deflation AGMG Solvers for Highly Ill-Conditioned Reservoir Simulation Problems. SPE Reservoir Simulation Symposium, SPE paper N. 105820-MS, Houston, TX, Feb. 26-28, 2007.
18. I. Koutis, G.L. Miller, A. Sinop, and D. Tolliver. Combinatorial Preconditioners and Multilevel Solvers for Problems in Computer Vision and Image Processing. Technical Report, Computer Science Dept., N. 1120, Carnegie Mellon University, 2009.
19. V. Kumar, A. Grama, A. Gupta and G. Karpis. Introduction to Parallel Computing.Addison Wesley, 2nd Edition, 2004.
20. R. Li and Y. Saad. GPU-Accelerated Preconditioned Iterative Linear Solvers. Technical Report, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, 2010.
21. R. Li, H. Klie, H. Sudan and Y. Saad. Towards Realistic Reservoir Simulations on Manycore Platforms. Submitted to SPEJ, 2010.
22. E. Lindholm, J. Nickolls, S. Oberman and J. Montrym. NVIDIA Tesla: A Unified Graphics and Computing Architecture. Micro, IEEE. 28:39-55, 2008. (Pubitemid 351796170)
23. R. Markovinovic and J.D. Jensen, Accelerating Iterative Solution Methods Using Reduced-Order Models as Solution Predictors. Int. Journal of Numerical Methods in Engineering, 68, 525-541, 2006. (Pubitemid 44612956)
24. P. Micikevicius. 3D Finite Difference Computation on GPUs Using CUDA. Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units, ACM, 79-84, 2009.
25. I. D. Mishev, N. Fedorova, S. Terekhov, B.L. Beckner, A.K. Usadi, M.B. Ray and O. Diyankov. Adaptive Control for Solver Performance Optimization in Reservoir Simulation. 11th European Conference on the Mathematics of Oil Recovery (ECMOR Xl), Bergen, Norway, Sept 8-11, 2008.
26. J. Nickolls, I.Buck, M. Garland and K. Skadron. Scalable Parallel Programming with CUDA. Queue, ACM. 6:40-53, 2008.
27. Y. Notay. Aggregation-Based Algebraic Multilevel Preconditioning. SlAM Journal on Matrix Analysis and Applications, 27: 998-1018, 2006.
28. Y. Saad. Iterative Methods for Sparse Linear Systems. 2nd edition, Society for Industrial and Applied Mathematics, Philadelphia, 2003.
29. G. Singh. Mimetic Finite Difference Method on GPU: Application in Reservoir Simulation and Well Modeling. Master Thesis, Department of Mathematical Sciences, Norwegian University of Science and Technology, Norway, July, 2010.
30. H. Sudan, H. Klie, R. Li and Y. Saad. High Performance Many Core Solvers for Reservoir Simulation, 12th European Conference on the Mathematics of Oil Recovery (ECMOR XII), Oxford, UK, Sept 6-9, 2010.
31. P. M. Vaidya. Solving Linear Equations with Symmetric Diagonally Dominant Matrices by Constructing Good Preconditioners. Unpublished manuscript UIUC 1990. A talk based on the manuscript was presented at the IMA Workshop on Graph Theory and Sparse Matrix Computation, Minneapolis, October 1991.
32. M. Wang, H. Klie, M. Parashar and H. Sudan. Solving Sparse Linear Systems on NVIDIA Tesla GPUs. Lecture Notes in Computer Science, Springer, 5544: 864-873, 2009.