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. ************

该提案是在开发更高效的存储系统时采用AI的一步。我们的目标是与高通加拿大公司的技术人员合作，开发能够使用最新机器学习创新技术的存储系统，以更智能地使用存储资源。*这样做的一种方式是将通信设备所需的信息的子集存储在存储器上。这个子集稍后将被智能系统用来构建完整的集合。机器学习解决方案将成为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CNNS）来构建一个系统，其中训练阶段将教系统如何使用部分数据集来生成缺失部分。然后将对系统进行测试和适当调整，以实现高精度和高效率。加拿大的高科技部门将受益于这一提案的调查结果，因为它提供了建立更好的存储系统的解决方案，几乎所有的技术公司都在使用这些系统。************