Implementing G-Machine in HyperLMNtal

TL;DR

This paper demonstrates the implementation of the G-machine, a lazy evaluation virtual machine, within HyperLMNtal, a hypergraph rewriting language, to address complex memory management in language processing systems.

Contribution

It introduces a novel approach of implementing a lazy evaluation machine using hypergraph rewriting, bridging language processing and graph rewriting techniques.

Findings

Successfully implemented G-machine in HyperLMNtal.

Showed potential for graph rewriting languages in language processing.

Enhanced understanding of memory management via graph models.

Abstract

Since language processing systems generally allocate/discard memory with complex reference relationships, including circular and indirect references, their implementation is often not trivial. Here, the allocated memory and the references can be abstracted to the labeled vertices and edges of a graph. And there exists a graph rewriting language, a programming language or a calculation model that can handle graph intuitively, safely and efficiently. Therefore, the implementation of a language processing system can be highly expected as an application field of graph rewriting language. To show this, in this research, we implemented G-machine, the virtual machine for lazy evaluation, in hypergraph rewriting language, HyperLMNtal.