A Distributed Block Approach to Solving Near-Block-Diagonal Systems with an Application to a Large Macroeconometric Model
This paper illustrates some benefits of small-scale distributed processing in solving nearblock-diagonal systems. We review the theoretical advantages of distributed block algorithms and apply such an algorithm to solve a large nonlinear macroeconometric model. For our application, on a four-processor UNIX server, the algorithm achieves a speedup factor of more than 6 over the standard algorithm on a single processor. A speedup factor of about 2 is due to the added efficiency of the block algorithm on a single processor, and the remaining factor of 3 results from distributing the work over four processors. Citation Copyright 1995 by Kluwer Academic Publishers.
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Volume (Year): 8 (1995)
Issue (Month): 4 (November)
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"Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models,"
Cowles Foundation Discussion Papers
564, Cowles Foundation for Research in Economics, Yale University.
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