ADVANCED PRODUCTION OUTPUT ENGINE FOR IMPLEMENTING PARALLEL COMPUTING

Abstract

Relevance. The paper discusses a theoretical approach to organizing parallel computing based on a
production model of data flow control. The production paradigm of parallel computing has the necessary
conditions for building new architectures and organizing high-performance parallel computing. We consider
production (mathematical) systems that control sets of left-hand sides of productions (samples). The
goal is to increase the efficiency of parallel inference of solutions by reducing unproductive time spent
searching through possible alternatives in the inference graph space. The research is based on the creation
of an extended symbolic computation machine for implementing parallel steps. A symbolic computing
machine is an abstract system that systematizes production output as a sequence of four computational
and search stages. The inference engine defines the general appearance of a homogeneous computing
system. The main difference is the decomposition of the base of production rules into separate subsets
based on the algebra of production and the structuring of relations between products. Instead of a single
“flat” structure, it is proposed to decompose the product base into parts - to introduce a system of independent
subsets of products. Parallel inference is implemented for individual subsets without loss of generality,
while the search for possible alternatives is reduced. Each subset of productions has a special
marker word, the value of which activates only one subset of productions. It is loaded into the operating
part of a homogeneous computing system for parallel execution. Results. It is shown that quantitative
estimates of the reduction in output time depend on the total number of productions, the number of subsets
formed and their size. Simulation has shown that even the simplest decomposition into two subsets (one subset consists of 2 productions) gives a time gain of (1.07-1.52) times, proportional to the total number of
productions. Conclusions. The created extended symbolic computing machine is the basis for the subsequent
creation of the architecture of a homogeneous computing system with a combination of centralized
and local control. This property allows computational units of a homogeneous operating part to work in
parallel without excessive access to shared memory.