The Autonomous Data Language -- Concepts, Design and Formal Verification

TL;DR

This paper introduces the data-autonomous paradigm for parallel programming, exemplified by AuDaLa, a language that enables natural programming and formal verification of highly parallel data collaboration.

Contribution

It proposes a novel data-autonomous paradigm, designs AuDaLa language, and provides formal semantics and verification methods for parallel programs.

Findings

AuDaLa enables natural programming in a data-autonomous style.

The formal semantics facilitate verification of parallel programs.

AuDaLa demonstrates effective data collaboration in parallel computing.

Abstract

Nowadays, the main advances in computational power are due to parallelism. However, most parallel languages have been designed with a focus on processors and threads. This makes dealing with data and memory in programs hard, which distances the implementation from its original algorithm. We propose a new paradigm for parallel programming, the data-autonomous paradigm, where computation is performed by autonomous data elements. Programs in this paradigm are focused on making the data collaborate in a highly parallel fashion. We furthermore present AuDaLa, the first data autonomous programming language, and provide a full formalisation that includes a type system and operational semantics. Programming in AuDaLa is very natural, as illustrated by examples, albeit in a style very different from sequential and contemporary parallel programming. Additionally, it lends itself for the formal verification of parallel programs, which we demonstrate.