We describe a static load balancing algorithm based on Kohonen Self-Organizing Maps (SOM) for a class of parallel computations where the communication pattern exhibits spatial locality and we present initial results. The topology preserving mapping achieved by SOM reduces the communication load across processors, however, it does not take load balancing into consideration. We introduce a load balancing mechanism into the SOM algorithm. We also present a preliminary multilevel implementation which resulted in significant execution time improvements. The results are promising to further improve SOM based load balancing for geometric graphs. © Springer-Verlag Berlin Heidelberg 2000
In this paper we study the problem of mapping a large class of irregular and loosely synchronous dat...
In this paper, LSOM (Load-balancing Self-Organizing Map), a neural network based on Kohonen's self-o...
The Kohonen self-organizing map (SOM),is a topology-preserving map that maps data from higher dimens...
To execute a parallel program on a multicomputer system, the tasks of the program have to be mapped ...
This paper presents self-organizing feature maps as an efficient tool generating solutions of the ma...
To execute a parallel program on a multicomputer system, the tasks of the program have to be mapped ...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
Ankara : The Department of Computer Engineering and Information Science and the Institute of Enginee...
We consider the problem of mapping large scale FEM graphs for the solution of partial differen...
A fundamental issue affecting the performance of a parallel application running on message-passing p...
Load imbalance in an application can lead to degradation of performance and a significant drop in sy...
. Parallelizing dynamic scientific applications involves solving the dynamic load balancing problem....
A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calcul...
The Flagship Parallel Reduction Machine is designed to execute declarative language programs based o...
This chapter describes a parallel optimization technique that incorporates a distributed load-balanc...
In this paper we study the problem of mapping a large class of irregular and loosely synchronous dat...
In this paper, LSOM (Load-balancing Self-Organizing Map), a neural network based on Kohonen's self-o...
The Kohonen self-organizing map (SOM),is a topology-preserving map that maps data from higher dimens...
To execute a parallel program on a multicomputer system, the tasks of the program have to be mapped ...
This paper presents self-organizing feature maps as an efficient tool generating solutions of the ma...
To execute a parallel program on a multicomputer system, the tasks of the program have to be mapped ...
Load balancing in large parallel systems with distributed memory is a difficult task often influenci...
Ankara : The Department of Computer Engineering and Information Science and the Institute of Enginee...
We consider the problem of mapping large scale FEM graphs for the solution of partial differen...
A fundamental issue affecting the performance of a parallel application running on message-passing p...
Load imbalance in an application can lead to degradation of performance and a significant drop in sy...
. Parallelizing dynamic scientific applications involves solving the dynamic load balancing problem....
A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calcul...
The Flagship Parallel Reduction Machine is designed to execute declarative language programs based o...
This chapter describes a parallel optimization technique that incorporates a distributed load-balanc...
In this paper we study the problem of mapping a large class of irregular and loosely synchronous dat...
In this paper, LSOM (Load-balancing Self-Organizing Map), a neural network based on Kohonen's self-o...
The Kohonen self-organizing map (SOM),is a topology-preserving map that maps data from higher dimens...