A distributed dynamic aspect machine for scientific software development

Authors:
Chanwit Kaewkasi;John R. Gurd
Affiliations:
University of Manchester;University of Manchester
Venue:
Proceedings of the 1st workshop on Virtual machines and intermediate languages for emerging modularization mechanisms
Year:
2007

Citing 11
Cited 2

Understanding Code Mobility

IEEE Transactions on Software Engineering
Parallel programming in OpenMP

Parallel programming in OpenMP
High Performance Fortran

IEEE Parallel & Distributed Technology: Systems & Technology
An Overview of AspectJ

ECOOP '01 Proceedings of the 15th European Conference on Object-Oriented Programming
Advice weaving in AspectJ

Proceedings of the 3rd international conference on Aspect-oriented software development
Using AspectJ to separate concerns in parallel scientific Java code

Proceedings of the 3rd international conference on Aspect-oriented software development
A semantics for advice and dynamic join points in aspect-oriented programming

ACM Transactions on Programming Languages and Systems (TOPLAS)
abc: an extensible AspectJ compiler

Proceedings of the 4th international conference on Aspect-oriented software development
HPC Productivity: An Overarching View

International Journal of High Performance Computing Applications
An execution layer for aspect-oriented programming languages

Proceedings of the 1st ACM/USENIX international conference on Virtual execution environments
A join point for loops in AspectJ

Proceedings of the 5th international conference on Aspect-oriented software development

Autonomous performance control of distributed applications in a heterogeneous environment

Proceedings of the 1st international conference on Autonomic computing and communication systems
Aspect-oriented support for synchronization in parallel computing

Proceedings of the 1st workshop on Linking aspect technology and evolution

Quantified Score

Hi-index	0.00

Visualization

Abstract

This position paper proposes the use of an event-based dynamic AOP machine as an infrastructure for interactive development of high performance scientific software. Advice codes in the proposed approach are similar to mobile agents that execute on distributed computational nodes. The key ideas underlying this approach are multi-level separation of parallelisation concerns and event-driven dynamic join points. The primary aim of the research is to use the AOP paradigm to improve productivity for scientific software development; the dynamic AOP machine is also expected to be further developed as an interactive computational grid.