Parallel Krylov Methods for Econometric Model Simulation

Authors:
Giorgio Pauletto;Manfred Gilli
Affiliations:
Hoover Institution, Stanford University, Stanford, CA 94305-6010, U.S.A.;Department of Econometrics, University of Geneva, 1211 Geneva 4, Switzerland
Venue:
Computational Economics - Special issue on computational studies at Cambridge
Year:
2000

Citing 6
Cited 1

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Abstract

This paper investigates parallel solution methods to simulate large-scalemacroeconometric models with forward-looking variables. The method chosen isthe Newton-Krylov algorithm, and we concentrate on a parallel solution to thesparse linear system arising in the Newton algorithm. We empirically analyzethe scalability of the GMRES method, which belongs to the class of so-calledKrylov subspace methods. The results obtained using an implementation of thePETSc 2.0 software library on an IBM SP2 show a near linear scalability forthe problem tested.