2025/06/24 by Tom T. P. Franken, Franken, Tom T. P., Thomas Neele +3
Business, Management and Accounting · Computer Science · Decision Sciences · #Advanced Database Systems and Queries #Business Process Modeling and Analysis #D.3.1 #Distributed #F.3.1 #F.3.2 #FOS: Computer and information sciences #Parallel #Programming Languages (cs.PL) #Scientific Computing and Data Management #and Cluster Computing (cs.DC)
paper · doi:10.48550/arxiv.2506.19457
openalex publication_date 2025/06/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.