A task allocation algorithm for distributed computing systems

Yau, Stephen S.; Satish, V.R.

doi:10.1109/cmpsac.1993.404238

Cited by 6 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For distributed CSs with static network structures (hypercube, 3D-torus or mesh) and SMP-clusters efficient algorithms for mapping parallel programs are developed (Ahmad, 1997), (Bokhari, 1981), (Lee, 1989), (Yau, 1993), (Yu, 2006), (Chen et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Mapping Parallel Programs Into Hierarchical Distributed Computer Systems

Khoroshevsky

Kurnosov

2009

Proceedings of the 4th International Conference on Software and Data Technologies

View full text Add to dashboard Cite

In most cases modern distributed computer systems (computer clusters and MPP systems) have hierarchical organization and non-uniform communication channels between elementary machines (computer nodes, processors or processor cores). Execution time of parallel programs significantly depends on how they map to computer system (on what elementary machines parallel processes are assigned and what channels for inter-process communications are used). The general problem of mapping a parallel program into a distributed computer system is a well known NP-hard problem and several heuristics have been proposed to approximate its optimal solution. In this paper an algorithm for mapping parallel programs into hierarchical distributed computer systems based on task graph partitioning is proposed. The software tool for mapping MPI applications into multicore computer clusters is considered. The quality of this algorithm with the NAS Parallel Benchmarks is evaluated.

show abstract

Section: Introductionmentioning

confidence: 99%

Mapping Parallel Programs Into Hierarchical Distributed Computer Systems

Khoroshevsky

Kurnosov

2009

Proceedings of the 4th International Conference on Software and Data Technologies

View full text Add to dashboard Cite

show abstract

“…After the implementation, we need to allocate the modules to processors in the ADS system. For the module allocation, we use the criteria of minimizing communication and balancing the load among the subsystems that constitute the distributed system [9]. Our module allocation algorithm is heuristic and suitable for allocating modules onto a distributed system whose subsystems are connected in the form of a LAN and communicating by means of broadcasting such as ADS.…”

Section: Implementation and Allocationmentioning

confidence: 99%

An object-oriented software development framework for autonomous decentralized systems

Yau

Yeom

Gao

et al.

Proceedings ISADS 95. Second International Symposium on Autonomous Decentralized Systems

Self Cite

View full text Add to dashboard Cite

Developing software for distributed computing systems is challenging due t o lack of good software development methodologies f o r distributed computing systems. It is very important t o develop reliable, adaptable and expandable application software for distributed computing systems. Autonomous Decentralized Systems (ADS is a on-line maintainability and fault-tolerance capability. In this paper, a framework f o r developing A D S application software is presented. Our framework consists of objectoriented requirements analysis, system design, implementation, allocation, verification .and maintenance. It is based on the object-oriented computation model developed f o r A D S application software development which supports on-line expandability and on-line modifiability. CASE environments for A D S software development are also discussed.

show abstract

Data Communication Analysis and Algorithm for the Efficiency of Data Distribution in High Performance Computing

Jiang

2008

2008 International Conference on Advanced Computer Theory and Engineering

View full text Add to dashboard Cite

A task allocation algorithm for distributed computing systems

Cited by 6 publications

References 12 publications

Mapping Parallel Programs Into Hierarchical Distributed Computer Systems

Mapping Parallel Programs Into Hierarchical Distributed Computer Systems

An object-oriented software development framework for autonomous decentralized systems

Data Communication Analysis and Algorithm for the Efficiency of Data Distribution in High Performance Computing

Contact Info

Product

Resources

About