Beyond arrays — A container-centric approach for parallelization of real-world symbolic applications

Abstract

Parallelization of symbolic applications is difficult and a systematic approach has yet to be developed. In this paper, we introduce the concept container, which refers to any general-purpose aggregate data type, such as matrices, lists, tables, graphs and I/O streams. We propose the container-centric approach, in which containers are treated by the compiler as built-in types. Containers become the target of data-parallelism and the focus of program analysis and transformations.