Distrim: Parallel GMM learning on multicore cluster
文献类型：会议论文
| 作者 | Renyong Yang; Tengke Xiong; Tao Chen; Zhexue Huang; Shengzhong Feng |
| 出版日期 | 2012 |
| 会议名称 | Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on |
| 会议地点 | 中国 |
| 英文摘要 | Learning GMM model on extreme large data is challenging. We provide theoretical support for the feasibility of parallel EM-based GMM learning via distributed computing, and also design and implement a distributed memory sharing GMM learning system on multicore clusters, which is named as Distrim. Distrim aims to maximize the usage of computational power and minimize the communication overheads as much as possible. The experimental results show that Distrim is much more efficient than Hadoop, and also has a good scalability with respect to the number of computing nodes. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4229]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2012 |
| 推荐引用方式 GB/T 7714 | Renyong Yang,Tengke Xiong,Tao Chen,et al. Distrim: Parallel GMM learning on multicore cluster[C]. 见:Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on. 中国. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。