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Tapping the supercomputer under your desk: Solving dynamic equilibrium models with graphics processors

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Author Info

  • Aldrich, Eric M.
  • Fernández-Villaverde, Jesús
  • Ronald Gallant, A.
  • Rubio-Ramírez, Juan F.

Abstract

This paper shows how to build algorithms that use graphics processing units (GPUs) installed in most modern computers to solve dynamic equilibrium models in economics. In particular, we rely on the compute unified device architecture (CUDA)Â of NVIDIA GPUs. We illustrate the power of the approach by solving a simple real business cycle model with value function iteration. We document improvements in speed of around 200 times and suggest that even further gains are likely.

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File URL: http://www.sciencedirect.com/science/article/B6V85-517BB1F-1/2/07bba84b275cbac9fbcc21bb42114def
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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 35 (2011)
Issue (Month): 3 (March)
Pages: 386-393

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Handle: RePEc:eee:dyncon:v:35:y:2011:i:3:p:386-393

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Web page: http://www.elsevier.com/locate/jedc

Related research

Keywords: CUDA Dynamic programming Parallelization Growth model Business cycles;

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References

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  1. S. Boragan Aruoba & Jesus Fernandez-Villaverde & Juan Francisco Rubio-Ramirez, 2003. "Comparing solution methods for dynamic equilibrium economies," Working Paper 2003-27, Federal Reserve Bank of Atlanta.
  2. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
  3. Judd, K.L., 1992. "Projection Methods for Saving Aggregate Growth Models," Working Papers e-92-7, Hoover Institution, Stanford University.
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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors
    by Christian Zimmermann in NEP-DGE blog on 2010-04-18 16:57:12
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:
  1. Olaf Posch & Timo Trimborn, 2011. "Numerical Solution of Dynamic Equilibrium Models under Poisson Uncertainty," CESifo Working Paper Series 3431, CESifo Group Munich.
  2. repec:pra:mprapa:21864 is not listed on IDEAS
  3. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, School of Economics and Management, University of Aarhus.
  4. Eric Aldrich, 2012. "Trading Volume in General Equilibrium with Complete Markets," 2012 Meeting Papers 36, Society for Economic Dynamics.
  5. Theodosios Dimopoulos & Stefano Sacchetto, . "Technological Heterogeneity and Corporate Investment," GSIA Working Papers 2012-E48, Carnegie Mellon University, Tepper School of Business.
  6. Grey Gordon, 2011. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," PIER Working Paper Archive 11-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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