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A hardware approach to value function iteration

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  • Peri, Alessandro

Abstract

This paper proposes a novel approach for the computation of dynamic stochastic equilibrium models. We design an FPGA specialized in the computation of a Bellman equation via value function iteration (VFI). Our hardware approach exhibits significant speed gains vis-à-vis GPU-based data-parallelization techniques. The speed gains arise from two layers of parallelism, accessible to hardware developers: instruction-level and pipeline parallelism at the logical resources level. By and large, the paper documents significant computational speed gains from hardware specialization, so far unexplored by the macroeconomic literature.

Suggested Citation

  • Peri, Alessandro, 2020. "A hardware approach to value function iteration," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
  • Handle: RePEc:eee:dyncon:v:114:y:2020:i:c:s0165188920300622
    DOI: 10.1016/j.jedc.2020.103894
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    References listed on IDEAS

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    7. 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.
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    Cited by:

    1. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana, 2020. "Uncertainty Shocks and Business Cycle Research," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 118-166, August.

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    More about this item

    Keywords

    FPGA; Dynamic programming; Pipelining; 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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