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Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors

Author

Listed:
  • Eric M. Aldrich
  • Jesus Fernandez-Villaverde
  • A. Ronald Gallant
  • Juan F. Rubio-Ramirez

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) 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.

Suggested Citation

  • Eric M. Aldrich & Jesus Fernandez-Villaverde & A. Ronald Gallant & Juan F. Rubio-Ramirez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," Working Papers 10-89, Duke University, Department of Economics.
  • Handle: RePEc:duk:dukeec:10-89
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    References listed on IDEAS

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    1. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    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, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    CUDA; Dynamic Programming; Parallelization; Growth Model; Business Cycles;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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