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This paper illustrates some benefits of small-scale distributed processing in solving near-block-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.

A distributed block approach to solving near-block-diagonal systems with an application to a large macroeconometric model