Customising application-specific multiprocessor systems: a case study

This paper reviews the development of application-specific multiprocessor systems for machine learning applications, and indicates how variants of such systems can be produced by design customisation. We first provide an overview of Progol, a machine learning framework based on inductive logic programming. We then describe, for such frameworks, various uniprocessor architectures and their adoption in multiprocessor systems. We also present the experimental facilities and results for evaluating our approach, and a method for automating the compilation of such designs.