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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- Ray C. Fair & John B. Taylor, 1980.
"Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models,"
NBER Technical Working Papers
0005, National Bureau of Economic Research, Inc.
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- Raymond Board & Peter A. Tinsley, 1996. "Smart systems and simple agents: industry pricing by parallel rules," Finance and Economics Discussion Series 1996-50, Board of Governors of the Federal Reserve System (U.S.).
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- Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(4), pages 711-734, May.
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