Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm

Michael C. Hatcher; Eric M. Scheffel

doi:10.1007/s10614-015-9537-0

Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm

Michael C. Hatcher, Eric M. Scheffel

School of Economics

Research output: Journal Publication › Article › peer-review

1 Citation (Scopus)

Abstract

This paper demonstrates the potential of graphics processing units in solving the incomplete markets model in parallel using the Krusell–Smith algorithm. We illustrate the power of this approach using the same exercise as in Den Haan et al. (J Econ Dyn Control 34:1–3, 2010). We document a speed gain which increases sharply with the number of agents. To reduce entry barriers, we explain our methodology and provide some example algorithms.

Original language	English
Pages (from-to)	569-591
Number of pages	23
Journal	Computational Economics
Volume	48
Issue number	4
DOIs	https://doi.org/10.1007/s10614-015-9537-0
Publication status	Published - 1 Dec 2016

Keywords

GPU computing
Heterogeneous agents
Incomplete markets
Interpolation
Krusell–Smith algorithm

ASJC Scopus subject areas

Economics, Econometrics and Finance (miscellaneous)
Computer Science Applications

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10.1007/s10614-015-9537-0

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abstract = "This paper demonstrates the potential of graphics processing units in solving the incomplete markets model in parallel using the Krusell–Smith algorithm. We illustrate the power of this approach using the same exercise as in Den Haan et al. (J Econ Dyn Control 34:1–3, 2010). We document a speed gain which increases sharply with the number of agents. To reduce entry barriers, we explain our methodology and provide some example algorithms.",

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Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm

Abstract

Keywords

ASJC Scopus subject areas

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