A parallel implementation of Boltzmann machine solving combinatorial optimization problems

In this paper we present an efficient way to implement the Boltzmann machine for solving combinatorial optimization problems on a distributed-memory multiprocessor (DMM), especially on a network of transputers. In this scheme, the neurons in a Boltzmann machine are partitioned into p disjoint sets and mapped onto each processor, where p is the number of processors in a DMM. Some experimental speedups together with analyses are also presented to demonstrate the usefulness of our parallelizing and implementation schemes.