LLC: A PARALLEL SKELETAL LANGUAGE

Author:

DORTA ANTONIO J.1,GONZÁLEZ JESÚS A.1,RODRÍGUEZ CASIANO1,DE SANDE FRANCISCO1

Affiliation:

1. Departamento de Estadística, I. O. y Computación, Universidad de La Laguna, c/ Astrofísico F. Sánchez s/n, 38271 La Laguna, Spain

Abstract

The skeletal approach to the development of parallel applications has been revealed to be one of the most successful and has been widely explored in the recent years. The goal of this approach is to develop a methodology of parallel programming based on a restricted set of parallel constructs. This paper presents llc, a parallel skeletal language, the theoretical model that gives support to the language and a prototype implementation for its compiler. The language is based on directives, uses a C-like syntax and gives support to the most widely used skeletal constructs. llCoMP is a source to source compiler for the language built on top of MPI. We evaluate the performance of our prototype compiler using four different parallel architectures and three algorithms. We present the results obtained in both shared and distributed memory architectures. Our model guarantees the portability of the language to any platform and its simplicity greatly eases its implementation.

Publisher

World Scientific Pub Co Pte Lt

Subject

Hardware and Architecture,Theoretical Computer Science,Software

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Разработка и применение вычислительной модели типовых решений. Пример использования «портфеля задач» для обучения нейронной сети HRBF;Вестник Самарского государственного технического университета. Серия «Физико-математические науки»;2014

2. Optimization strategies in different CUDA architectures using llCoMP;Microprocessors and Microsystems;2012-03

3. Automatic code generation for GPUs in llc;The Journal of Supercomputing;2011-03-15

4. A survey of algorithmic skeleton frameworks: high-level structured parallel programming enablers;Software: Practice and Experience;2010-11

5. Software Architectures for Flexible Task-Oriented Program Execution on Multicore Systems;Complex Systems Design & Management;2010

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