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Solving Dynamic Programming Problems on a Computational Grid

Author

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  • Yongyang Cai
  • Kenneth L. Judd
  • Greg Thain
  • Stephen J. Wright

Abstract

We implement a dynamic programming algorithm on a computational grid consisting of loosely coupled processors, possibly including clusters and individual workstations. The grid changes dynamically during the computation, as processors enter and leave the pool of workstations. The algorithm is implemented using the Master-Worker library running on the HTCondor grid computing platform. We implement value function iteration for several large dynamic programming problems of two kinds: optimal growth problems and dynamic portfolio problems. We present examples that solve in hours on HTCondor but would take weeks if executed on a single workstation. The use of HTCondor can increase a researcher's computational productivity by at least two orders of magnitude.

Suggested Citation

  • Yongyang Cai & Kenneth L. Judd & Greg Thain & Stephen J. Wright, 2013. "Solving Dynamic Programming Problems on a Computational Grid," NBER Working Papers 18714, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18714
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    References listed on IDEAS

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    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Mathur, Sudhanshu & Morozov, Sergei, 2009. "Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control," MPRA Paper 16721, University Library of Munich, Germany.
    3. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, January.
    4. Juillard, Michel & Villemot, Sébastien, 2011. "Multi-country real business cycle models: Accuracy tests and test bench," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 178-185, February.
    5. Sergei Morozov & Sudhanshu Mathur, 2012. "Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 151-182, August.
    6. J. Rust & J. F. Traub & H. Wozniakowski, 2002. "Is There a Curse of Dimensionality for Contraction Fixed Points in the Worst Case?," Econometrica, Econometric Society, vol. 70(1), pages 285-329, January.
    7. Michael Creel & William Goffe, 2008. "Multi-core CPUs, Clusters, and Grid Computing: A Tutorial," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 353-382, November.
    8. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    9. Aldrich, Eric M. & Fernández-Villaverde, Jesús & Ronald Gallant, A. & Rubio-Ramírez, Juan F., 2011. "Tapping the supercomputer under your desk: Solving dynamic equilibrium models with graphics processors," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 386-393, March.
    10. Den Haan, Wouter J. & Judd, Kenneth L. & Juillard, Michel, 2011. "Computational suite of models with heterogeneous agents II: Multi-country real business cycle models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 175-177, February.
    11. Cai, Yongyang & Judd, Kenneth L. & Lontzek, Thomas S. & Michelangeli, Valentina & Su, Che-Lin, 2017. "A Nonlinear Programming Method For Dynamic Programming," Macroeconomic Dynamics, Cambridge University Press, vol. 21(02), pages 336-361, March.
    12. repec:spr:compst:v:77:y:2013:i:3:p:407-421 is not listed on IDEAS
    13. Yongyang Cai & Kenneth Judd, 2013. "Shape-preserving dynamic programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 407-421, June.
    14. John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
    15. Yongyang Cai & Kenneth Judd, 2015. "Dynamic programming with Hermite approximation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(3), pages 245-267, June.
    16. Yongyang Cai & Kenneth L. Judd, 2010. "Stable and Efficient Computational Methods for Dynamic Programming," Journal of the European Economic Association, MIT Press, vol. 8(2-3), pages 626-634, 04-05.
    17. Michael Creel, 2005. "User-Friendly Parallel Computations with Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 26(2), pages 107-128, October.
    18. Yongyang Cai & Kenneth L. Judd & Rong Xu, 2013. "Numerical Solution of Dynamic Portfolio Optimization with Transaction Costs," NBER Working Papers 18709, National Bureau of Economic Research, Inc.
    19. Cai, Yongyang & Judd, Kenneth L., 2012. "Dynamic programming with shape-preserving rational spline Hermite interpolation," Economics Letters, Elsevier, vol. 117(1), pages 161-164.
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    Citations

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    Cited by:

    1. Yongyang Cai & Kenneth L. Judd & Thomas S. Lontzek, 2015. "The Social Cost of Carbon with Economic and Climate Risks," Papers 1504.06909, arXiv.org, revised Apr 2015.
    2. Yongyang Cai & Kenneth Judd, 2015. "Dynamic programming with Hermite approximation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(3), pages 245-267, June.
    3. Cai, Yongyang & Steinbuks, Jevgenijs & Elliott, Joshua & Hertel, Thomas W., 2014. "The effect of climate and technological uncertainty in crop yields on the optimal path of global land use," Policy Research Working Paper Series 7009, The World Bank.
    4. Lilia Maliar, 2013. "Assessing gains from parallel computation on supercomputers," Working Papers. Serie AD 2013-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    5. Cerqueti, Roy & Quaranta, Anna Grazia & Ventura, Marco, 2016. "Innovation, imitation and policy inaction," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 22-30.
    6. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2016. "Dynamic Portfolio Optimization with Liquidity Cost and Market Impact: A Simulation-and-Regression Approach," Papers 1610.07694, arXiv.org, revised Oct 2017.
    7. Cai, Yongyang & Brock, William & Xepapadeas, Anastasios, 2016. "Climate Change Economics and Heat Transport across the Globe: Spatial-DSICE," 2017 Allied Social Science Association (ASSA) Annual Meeting, January 6-8, 2017, Chicago, Illinois 251833, Agricultural and Applied Economics Association.

    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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