Low-level functional GPU programming for parallel algorithms

TY - GEN

T1 - Low-level functional GPU programming for parallel algorithms

AU - Dybdal, Martin

AU - Elsman, Martin

AU - Svensson, Bo Joel

AU - Sheeran, Mary

N1 - Conference code: 5

PY - 2016/9/8

Y1 - 2016/9/8

N2 - 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 self-contained, 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.

AB - 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 self-contained, 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.

KW - GPU programming, Type systems, array-programming, data-parallel languages, hierarchical machine models, iteration schemes, pull-arrays, push-arrays

U2 - 10.1145/2975991.2975996

DO - 10.1145/2975991.2975996

M3 - Article in proceedings

SN - 978-1-4503-4433-3

SP - 31

EP - 37

BT - Proceedings of the 5th International Workshop on Functional High-Performance Computing

PB - Association for Computing Machinery

T2 - 5th International Workshop on Functional High-Performance Computing

Y2 - 22 September 2016 through 22 September 2016

ER -