A collection-oriented programming model for performance portability

This paper describes Surge, a collection-oriented programming model that enables programmers to compose parallel computations using nested high-level data collections and operators. Surge exposes a code generation interface, decoupled from the core computation, that enables programmers and autotuners to easily generate multiple implementations of the same computation on various parallel architectures such as multi-core CPUs and GPUs. By decoupling computations from architecture-specific implementation, programmers can target multiple architectures more easily, and generate a search space that facilitates optimization and customization for specific architectures. We express in Surge four real-world benchmarks from domains such as sparse linear-algebra and machine learning and from the same performance-portable specification, generate OpenMP and CUDA C++ implementations.

• Type: Journal
• Year: 2015
• Where: PPOPP
• Authors: Saurav Muralidharan, Michael Garland, Bryan C. Catanzaro, Albert Sidelnik, Mary W. Hall
• Keywords: Distributed And Parallel Computing, PPOPP 2015