CSR: Small: Prediction-Based Data Placement for New Memory and Storage Hierarchies

CSR：小型：新内存和存储层次结构的基于预测的数据放置

• 批准号: 1217569
• 负责人: David Du
• 金额: $ 45万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1217569&HistoricalAwards=false
• 关键词: CSR; Small; Prediction; Based; Data

Many high-end computing and data-intensive applications, such as transaction processing systems, large-scale scientific simulations, and on-demand services, are limited by the performance of the underlying memory and storage systems. The goal of this project is to improve the memory/storage hierarchy by integrating new and emerging memory/storage technologies with the existing memory/storage hierarchy. Flash memory based Solid State Drives (SSDs) and Phase Change Memory (PCM) are two emerging memory/storage technologies that show tremendous promise to improve the performance of current computer systems. Shingled Write Disks (SWDs) have been recently proposed to further improve the magnetic disk space capacity to another level. This project is to investigate effective data placement in the new memory/storage hierarchies to better support high-end computing and data-intensive applications. Considering the special characteristics of these new technologies, this project provides innovative solutions for prediction-based data placement in the new memory/storage hierarchies to effectively improve the performance of both memory and storage data accesses. It speeds up the integration of PCM with DRAM as a new memory hierarchy and flash memory-based SSDs and SWDs with the existing storage hierarchy. Providing efficient solutions to the fundamental performance issues greatly improves the performance of many critical applications including weather forecasting, large-scale scientific simulations, e-commerce, etc. Therefore, the project makes huge impact on our daily life. Quickly integrating SWDs into the existing storage hierarchy will also enhance our capability to handle huge amounts of available data. This project creates positive impact on every layer of the memory and storage hierarchies.

许多高端计算和数据密集型应用，例如事务处理系统、大规模科学模拟和按需服务，都受到底层内存和存储系统性能的限制。该项目的目标是通过将新兴的内存/存储技术与现有的内存/存储层次结构相集成来改进内存/存储层次结构。 基于闪存的固态硬盘 (SSD) 和相变存储器 (PCM) 是两种新兴的内存/存储技术，在提高当前计算机系统的性能方面显示出巨大的前景。最近提出了叠瓦写盘(SWD)以将磁盘空间容量进一步提高到另一个水平。该项目旨在研究新内存/存储层次结构中的有效数据放置，以更好地支持高端计算和数据密集型应用程序。考虑到这些新技术的特殊性，该项目为新的内存/存储层次结构中基于预测的数据放置提供了创新的解决方案，以有效提高内存和存储数据访问的性能。它加速了 PCM 与 DRAM 作为新的存储层次结构以及基于闪存的 SSD 和 SWD 与现有存储层次结构的集成。为基本性能问题提供有效的解决方案，极大地提高了许多关键应用的性能，包括天气预报、大规模科学模拟、电子商务等。因此，该项目对我们的日常生活产生了巨大影响。将 SWD 快速集成到现有的存储层次结构中也将增强我们处理大量可用数据的能力。该项目对内存和存储层次结构的每一层都产生了积极的影响。