Pluggable parallelisation

Abstract

This paper presents the concept of pluggable parallelisation that allows scientists to develop "sequential like" codes that can take advantage of multi-core, cluster and grid systems. In this approach parallel applications are developed by plugging parallelisation patterns/idioms into scientific codes (e.g., "sequential like" codes), softening the move from sequential to parallel programming and promoting the separation between domain specific code and parallelisation issues. Pluggable parallelisation combines three characteristics: 1) parallelisation is performed from "outside to inside", localising parallelisation concerns into well defined modules, reducing changes required to the domain specific code and avoiding invasive parallelisation of base code; 2) control view is separated from data view promoting a stronger separation of concerns which improves reuse of parallelisation concerns across platforms and enables fine-grained refinements; and 3) abstractions can be composed, supporting the development of more complex patterns based on fine-grained features. This paper presents the concept of pluggable parallelisation and shows how some well-known parallelisation strategies can be implemented in this approach. Results show that this is a feasible approach and performance is competitive with traditional parallel programming.

AOmpLib: An Aspect Library for Large-Scale Multi-core Parallel Programming

“…[13] provides a template-based language aiming to encapsulate different parallelisation concerns into different modules. The work in [9] showed how several concurrency patterns and mechanisms could be encapsulated into reusable aspect modules.…”

@Java

“…Let us see a practical example where this capability finds application. Several authors explored the topic of automating the parallelization of a serial loop (e.g., [9,11]). There are also solutions that employ an annotation system (e.g., @CUDA [6]).…”

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“…its pure behavior) and the Grid-specific behavior [23,33,19]. This is commonly achieved via aspect-oriented programming (AOP) [28] techniques, whereby a sequential code is attached one or more ''aspects'' that encapsulate how the different portions of this code are executed in parallel within a Grid.…”