@inproceedings{d2d0b71ff49c4006b13e3b9fd79c221d,
title = "A GPU-accelerated large-scale music similarity retrieval method",
abstract = "High-quality content-based music similarity retrieval methods are non-vectorial and use non-metric divergence measures, which prevents the expansion of music recommendation systems. We presents a GPU-based method to speed up content-based music similarity search in large-scale collections, in order to improve the response speed without reducing retrieval accuracy. The method also introduce an optimization technique based on memory layout to improve memory access. The efficiency of our method is validated through extensive experiments. Evaluation results show that our single GPU implementation achieves 10x speedup ratio on NVIDIA GTX480, when compared to a typical general purpose CPU's execution time.",
keywords = "CUDA, GPU, Music recommendation, Music similarity retrieval",
author = "Limin Xiao and Yao Zheng and Wenqi Tang and Guangchao Yao and Li Ruan and Xiang Wang",
year = "2013",
doi = "10.1109/GreenCom-iThings-CPSCom.2013.341",
language = "英语",
isbn = "9780769550466",
series = "Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013",
pages = "1839--1843",
booktitle = "Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013",
note = "2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013 ; Conference date: 20-08-2013 Through 23-08-2013",
}