GPGPU Kernel Implementation and Refinement using Obsidian

• Obsidian is a domain specific language for data-parallel programming on graphics processors (GPUs). It is em-bedded in the functional programming language Haskell. The user writes code using constructs familiar from Haskell(like map and reduce), recursion and some specially designed combinators for combining GPU programs. NVIDIACUDA code is generated from these high level descriptions, and passed to the nvcc compiler [1]. Currently, weconsider only the generation of single kernels, and not their coordination.This paper is focussed on how the user should work with Obsidian, starting with an obviously correct (or well-tested) description of the required function, and refining it by the introduction of constructs to give finer control of thecomputation on the GPU. For some combinators, this approach results in CUDA code with satisfactory performance,promising increased productivity, as the high level descriptions are short and uncluttered. But for other combinators,the performance of generated code is not yet satisfactory. Ways to tackle this problem and plans to integrate Obsidianwith another higher-level embedded language for GPU programming in Haskell are briefly discussed.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Engineering (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

GPUs

GPGPU

Haskell

Embedded language

Data-parallel

Publication and Content Type

kon (subject category)

ref (subject category)