@inproceedings{38084c918f4046b3a73f048a606a576e,
title = "Efficient parallel algorithm for compound comparisons on multi-GPUs",
abstract = "Compound comparison is an important task for computational chemistry. By the comparison reulsts, potential inhibitors can be found and then used for the following experiments. The time complexity of a pairwise compound comparison is O(n2), where n is the maximal length of compounds. In general, the compound length is small, and the cost of computation time is short. However, more and more compounds have been synthesized and extracted now, even more than ten of millions. Therefore, it still will be time-consuming when comparing with a large amount of compounds (multiple compound comparisons). In this paper, we propose a parallel algorithm for multiple compound comparisons on multi-GPUs. Four load-balancing strategies were considered in the proposed algorithm in order to accelerate the computation speed among thread blocks on GPUs. The proposed algorithm was implemented by C+OpenMP+CUDA, and achieved more than 50 times speedup by comparing with its CPU version under the experiemtal results.",
keywords = "Compound comparison, CUDA, Load-Balancing, OpenMP, SMILES",
author = "Lin, {Chun Yuan} and Wang, {Chung Hung} and Hung, {Che Lun} and Lin, {Yu Shiang}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; null ; Conference date: 02-11-2014 Through 05-11-2014",
year = "2014",
month = dec,
day = "29",
doi = "10.1109/BIBM.2014.6999307",
language = "English",
series = "Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "30--35",
editor = "Huiru Zheng and Hu, {Xiaohua Tony} and Daniel Berrar and Yadong Wang and Werner Dubitzky and Jin-Kao Hao and Kwang-Hyun Cho and David Gilbert",
booktitle = "Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014",
address = "United States",
}