Low-Level Functional GPU Programming for Parallel Algorithms
Paper in proceedings, 2016

We present a Functional Compute Language (FCL) for low-level GPU programming. FCL is functional in style, which allows for easy composition of program fragments and thus easy prototyping and a high degree of code reuse. In contrast with projects such as Futhark, Accelerate, Harlan, Nessie and Delite, the intention is not to develop a language providing fully automatic optimizations, but instead to provide a platform that supports absolute control of the GPU computation and memory hierarchies. The developer is thus required to have an intimate knowledge of the target platform, as is also required when using CUDA/OpenCL directly. FCL is heavily inspired by Obsidian. However, instead of relying on a multi-staged meta-programming approach for kernel generation using Haskell as meta-language, FCL is completely selfcontained, and we intend it to be suitable as an intermediate language for data-parallel languages, including data-parallel parts of high-level array languages, such as R, Matlab, and APL. We present a type-system and a dynamic semantics suitable for understanding the performance characteristics of both FCL and Obsidian-style programs. Our aim is that FCL will be useful as a platform for developing new parallel algorithms, as well as a target language for various code-generators targeting GPU hardware.

Author

Martin Dybdal

Martin Elsman

Joel Bo Svensson

Chalmers, Computer Science and Engineering (Chalmers), Software Technology (Chalmers)

Mary Sheeran

Chalmers, Computer Science and Engineering (Chalmers), Software Technology (Chalmers)

Int. Workshop on Functional High Performance Computing, associated with Int. Conf. on Functional Programming

31-37

Areas of Advance

Information and Communication Technology

Subject Categories

Computer and Information Science

Software Engineering

Computer Science

More information

Created

10/7/2017