Obsidian: A Domain Specific Embedded Language for Parallel Programming of Graphics Processors

Svensson, Joel; Sheeran, Mary; Claessen, Koen

doi:10.1007/978-3-642-24452-0_9

Cited by 30 publications

(24 citation statements)

References 14 publications

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“…Obsidian [21] is another Haskell library for GPU programming. The design of Obsidian is quite different from that of Accelerate: in Obsidian, users can specify low-level GPU manipulation.…”

Section: Obsidianmentioning

confidence: 99%

“…Functional programming is often said to be highly productive due to the strong modularity of functional languages [8]. In the area of functional programming, several languages or libraries for parallel computing have been developed actively [3], [5], [9], [10], [11], [12], [14], [19], [21].…”

Section: Introductionmentioning

confidence: 99%

“…Another important aspect of Haskell matsuzaki.kiminori@kochi-tech.ac.jp is that the user community has developed quite a few libraries. For instance, we have the following libraries for parallel computation: Control.Parallel [14] enables parallel computation by changing the evaluation order, Repa (regular parallel arrays) [9] helps parallel computation over multi-dimensional arrays, Accelerate [3] and Obsidian [21] enable parallel computing with GPUs, and Eden [11] provides parallel computation patterns as algorithmic skeletons.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Libraries for Parallel Computing in Haskell — A Case Study with a Super-resolution Application

Matsumoto

Matsuzaki

2017

Journal of Information Processing

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Abstract:Haskell is a functional language featuring lazy evaluation and referential transparency. On one hand, Referential transparency is useful for parallel computing because the results do not depend on the evaluation order, but on the other hand, parallel computing requires an evaluation order that is different from that of lazy evaluation. There are some parallel programming libraries for Haskell, such as Repa (regular parallel arrays) and Accelerate. However, little research has been conducted on evaluation with real applications, and the usefulness of these libraries remains unclear. In this study, we evaluated the usefulness of parallel programming libraries for Haskell with an application that applies a super-resolution technique to fMRI images. We developed a CPU-based parallel program with Repa and GPU-based parallel program with Accelerate and compared their performance. We obtained reasonable speedups for the program with Repa, but not for the program with Accelerate. We also investigated Accelerate's performance issues with an implementation in C and CUDA and the log from the Accelerate program. In this paper, we report our findings through a case study, focusing on the advantages and difficulties in parallel program development with Haskell.

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“…Obsidian [21] is another Haskell library for GPU programming. The design of Obsidian is quite different from that of Accelerate: in Obsidian, users can specify low-level GPU manipulation.…”

Section: Obsidianmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of Libraries for Parallel Computing in Haskell — A Case Study with a Super-resolution Application

Matsumoto

Matsuzaki

2017

Journal of Information Processing

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“…Obsidian [42] and Harlan [24] are earlier projects with similar goals. Obsidian exposes more details of the underlying GPU hardware to the programmer.…”

Section: Related Workmentioning

confidence: 99%

Generating performance portable code using rewrite rules: from high-level functional expressions to high-performance OpenCL code

SteuwerMichel¹,

FenschChristian²,

LindleySam³

et al. 2015

SIGPLAN Not.

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Computers have become increasingly complex with the emergence of heterogeneous hardware combining multicore CPUs and GPUs. These parallel systems exhibit tremendous computational power at the cost of increased programming effort resulting in a tension between performance and code portability. Typically, code is either tuned in a low-level imperative language using hardware-specific optimizations to achieve maximum performance or is written in a high-level, possibly functional, language to achieve portability at the expense of performance.We propose a novel approach aiming to combine high-level programming, code portability, and high-performance. Starting from a high-level functional expression we apply a simple set of rewrite rules to transform it into a low-level functional representation, close to the OpenCL programming model, from which OpenCL code is generated. Our rewrite rules define a space of possible implementations which we automatically explore to generate hardware-specific OpenCL implementations. We formalize our system with a core dependently-typed λ-calculus along with a denotational semantics which we use to prove the correctness of the rewrite rules.We test our design in practice by implementing a compiler which generates high performance imperative OpenCL code. Our experiments show that we can automatically derive hardwarespecific implementations from simple functional high-level algorithmic expressions offering performance on a par with highly tuned code for multicore CPUs and GPUs written by experts.

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“…Haskell has proved very effective as a host language for embedding domain specific languages. Examples include [1,3,7,13,17,20].…”

Section: Related Workmentioning

confidence: 99%

An EDSL approach to high performance Haskell programming

Ankner

Svenningsson

2013

Proceedings of the 2013 ACM SIGPLAN Symposium on Haskell

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This paper argues for a new methodology for writing high performance Haskell programs by using Embedded Domain Specific Languages.We exemplify the methodology by describing a complete library, meta-repa, which is a reimplementation of parts of the repa library. The paper describes the implementation of meta-repa and contrasts it with the standard approach to writing high performance libraries. We conclude that even though the embedded language approach has an initial cost of defining the language and some syntactic overhead it gives a more tailored programming model, stronger performance guarantees, better control over optimizations, simpler implementation of fusion and inlining and allows for moving type level programming down to value level programming in some cases. We also provide benchmarks showing that meta-repa is as fast, or faster, than repa.Furthermore, meta-repa also includes push arrays and we demonstrate their usefulness for writing certain high performance kernels such as FFT.

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Obsidian: A Domain Specific Embedded Language for Parallel Programming of Graphics Processors

Cited by 30 publications

References 14 publications

Evaluation of Libraries for Parallel Computing in Haskell — A Case Study with a Super-resolution Application

Evaluation of Libraries for Parallel Computing in Haskell — A Case Study with a Super-resolution Application

Generating performance portable code using rewrite rules: from high-level functional expressions to high-performance OpenCL code

An EDSL approach to high performance Haskell programming

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