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Parallel Krylov Methods for Econometric Model Simulation

  • Giorgio Pauletto
  • Manfred Gilli

This paper investigates parallel solution methods to simulate large-scale macroeconometric models with forward-looking variables. The method chosen is the Newton-Krylov algorithm, and we concentrate on a parallel solution to the sparse linear system arising in the Newton algorithm. We empirically analyze the scalability of the GMRES method, which belongs to the class of so-called Krylov subspace methods. The results obtained using an implementation of the PETSc 2.0 software library on an IBM SP2 show a near linear scalability for the problem tested.

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Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 16 (2000)
Issue (Month): 1/2 (October)
Pages: 173-186

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Handle: RePEc:kap:compec:v:16:y:2000:i:1/2:p:173-186
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=100248
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