Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era

并行分布式机器学习——多核时代的智能数据分析

• 批准号: DP0987773
• 负责人: Prof Alistair Rendell
• 金额: $ 24.93万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2009
• 资助国家: 澳大利亚
• 起止时间: 2009-10-30 至 2015-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0987773
• 关键词: Parallel; Distributed; Machine; Learning; Smart

In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.

在大型数据中心，我们的研究将通过使用图形卡来降低能耗，图形卡的计算功率比比传统处理器好得多。在台式计算机上，它将使机器学习变得实用，使垃圾邮件过滤和内容分析的有效算法成为可能。在网络系统上，它将导致分布式推理，缓存和协同过滤应用程序，这将减少所需的带宽，并使互联网对用户更安全。最后，它将使监测和探测传感器网络的快速部署成为可能，例如用于环境监测和保护澳大利亚的边界。