Storage saving using CNNs**********

使用 CNN 节省存储************

• 批准号: 536854-2018
• 负责人: Baniasadi, Amirali
• 金额: $ 1.82万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644578
• 关键词: Storage; saving; using; CNNs

This proposal is a step towards employing AI in developing more efficient storage systems. The goal is to collaborate with technical staff from Qualcomm Canada to develop storage systems capable of using the latest machine learning innovations to use storage resources more intelligently.****One way to do so is to store a subset of the information needed by communication devices on the storage. This subset will be used later by an intelligent system to build the complete set. Machine learning solutions will serve at the core of this intelligent system. ****This proposal suggests using Convolutional Neural Networks (or simply CNNS) to build a system where a training phase will teach the system how to use part of the data set to produce the missing portion. The system will then be tested and properly tuned to achieve high accuracy and efficiency.****Canada's high-tech sector will benefit from the findings of this proposal as it provides solutions to building better storage systems which are virtually used by all technological companies. ************

该建议是迈向开发更有效的存储系统的一步。目的是与加拿大高通的技术人员合作，以开发能够使用最新机器学习创新来更智能地使用存储资源的存储系统。该子集将稍后由智能系统使用以构建完整的集合。机器学习解决方案将服务于这个智能系统的核心。 ****该提案建议使用卷积神经网络（或简称CNN）构建一个系统，在该系统中，训练阶段将教导系统如何使用部分数据集来产生缺失部分。然后，该系统将经过测试并进行适当调整以实现高精度和效率。 ************