Bulk Synchronous Parallel ML: Modular Implementation and Performance Prediction

Loulergue, Frédéric; Gava, Frédéric; Billiet, David

doi:10.1007/11428848_132

Cited by 59 publications

(30 citation statements)

References 14 publications

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“…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%

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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Section: Introductionmentioning

confidence: 99%

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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“…We used the BSML implementation [15] of a program [3] that benchmarks and determines the BSP parameters of our machine (16 Pentium IV 2.8 Ghz, 1 Gb RAM nodes cluster interconnected with a Gigabyte Ethernet network). We then compute these parameters for 3 libraries, corresponding to 2 different implementations of BSML: MPICH, OPEN-MPI 5 and PUB [4].…”

Section: Computation Of the Bsp Parametersmentioning

confidence: 99%

BSP Functional Programming: Examples of a Cost Based Methodology

Gava

2008

Computational Science – ICCS 2008

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“…-the support of list homomorphisms in SyDPaCC that previously only supported BSP homomorphisms [14] and the GTA paradigm [7], -improvements of the formalisation of the parallel functional language Bulk Synchronous Parallel ML (BSML) [13] and algorithmic skeletons in Coq, -an application of the framework to produce a parallel program for the maximum prefix sum problem.…”

Section: Introductionmentioning

confidence: 99%

Calculating Parallel Programs in Coq Using List Homomorphisms

Loulergue

Bousdira

Tesson

2016

Int J Parallel Prog

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SyDPaCC is a set of libraries for the Coq proof assistant. It allows to write naive functional programs (i.e. with high complexity) that are considered as specifications, and to transform them into more efficient versions. These more efficient versions can then be automatically parallelised before being extracted from Coq into source code for the functional language OCaml together with calls to the Bulk Synchronous Parallel ML library. In this paper we present a new core version of SyDPaCC for the development of parallel programs correct-by-construction using the theory of list homomorphisms and algorithmic skeletons implemented and verified in Coq. The framework is illustrated on the maximum prefix sum problem.

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Bulk Synchronous Parallel ML: Modular Implementation and Performance Prediction

Cited by 59 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

BSP Functional Programming: Examples of a Cost Based Methodology

Calculating Parallel Programs in Coq Using List Homomorphisms

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