Non procedural language for parallel programs

TL;DR

This paper explores non-procedural languages for parallel programming, analyzing formal systems, algorithm complexity, and the flexibility of data set definitions to enhance parallel program development.

Contribution

It introduces a formal framework for non-procedural parallel languages, examining their expressive power, algorithmic complexity, and data set definition flexibility.

Findings

Formal systems effectively define named datasets

Algorithm complexity varies with data set definitions

Non-procedural languages offer flexible parallel programming models

Abstract

Probably building non procedural languages is the most prospective way for parallel programming just because non procedural means no fixed way for execution. The article consists of 3 parts. In first part we consider formal systems for definition a named datasets and studying an expression power of different subclasses. In the second part we consider a complexity of algorithms of building sets by the definitions. In third part we consider a fullness and flexibility of the class of program based data set definitions.