1995
Ahrens, James; Hansen, Charles
Cost-effective data-parallel load balancing Proceedings Article
In: ICPP (2), pp. 218–221, 1995, (LA-UR-95-1462).
Abstract | Links | BibTeX | Tags: data-parallel, load balancing
@inproceedings{ahrens1995cost,
title = {Cost-effective data-parallel load balancing},
author = {James Ahrens and Charles Hansen},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/Cost-EffectiveData-ParallelLoadBalancing.pdf},
year = {1995},
date = {1995-01-01},
booktitle = {ICPP (2)},
pages = {218--221},
abstract = {Load balancing algorithms improve a program’s performance on unbalanced datasets, but can degrade performance on balanced datasets, because unnecessary load redistributions occur. This paper presents a cost-effective data-parallel load balancing algorithm which performs load redistributions only when the possible savings outweigh the redistribution costs. Experiment s with a data-parallel polygon renderer show a performance improvement of up to a factor of 33 on unbalanced datasets and a maximum performance loss of only 27 percent on balanced datasets when using this algorithm.},
note = {LA-UR-95-1462},
keywords = {data-parallel, load balancing},
pubstate = {published},
tppubtype = {inproceedings}
}
Load balancing algorithms improve a program’s performance on unbalanced datasets, but can degrade performance on balanced datasets, because unnecessary load redistributions occur. This paper presents a cost-effective data-parallel load balancing algorithm which performs load redistributions only when the possible savings outweigh the redistribution costs. Experiment s with a data-parallel polygon renderer show a performance improvement of up to a factor of 33 on unbalanced datasets and a maximum performance loss of only 27 percent on balanced datasets when using this algorithm.
: . .
1.
Ahrens, James; Hansen, Charles
Cost-effective data-parallel load balancing Proceedings Article
In: ICPP (2), pp. 218–221, 1995, (LA-UR-95-1462).
@inproceedings{ahrens1995cost,
title = {Cost-effective data-parallel load balancing},
author = {James Ahrens and Charles Hansen},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/Cost-EffectiveData-ParallelLoadBalancing.pdf},
year = {1995},
date = {1995-01-01},
booktitle = {ICPP (2)},
pages = {218--221},
abstract = {Load balancing algorithms improve a program’s performance on unbalanced datasets, but can degrade performance on balanced datasets, because unnecessary load redistributions occur. This paper presents a cost-effective data-parallel load balancing algorithm which performs load redistributions only when the possible savings outweigh the redistribution costs. Experiment s with a data-parallel polygon renderer show a performance improvement of up to a factor of 33 on unbalanced datasets and a maximum performance loss of only 27 percent on balanced datasets when using this algorithm.},
note = {LA-UR-95-1462},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Load balancing algorithms improve a program’s performance on unbalanced datasets, but can degrade performance on balanced datasets, because unnecessary load redistributions occur. This paper presents a cost-effective data-parallel load balancing algorithm which performs load redistributions only when the possible savings outweigh the redistribution costs. Experiment s with a data-parallel polygon renderer show a performance improvement of up to a factor of 33 on unbalanced datasets and a maximum performance loss of only 27 percent on balanced datasets when using this algorithm.