CSR: Medium: WasteNot: Streamlining Virtual Memory for Modern Systems

CSR：中：WasteNot：简化现代系统的虚拟内存

基本信息

批准号：
1302260
负责人：
Michael Swift
金额：
$ 74.91万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2016-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1302260&HistoricalAwards=false
关键词：
CSR Medium WasteNot Streamlining Virtual

项目摘要

This proposal attacks waste in virtual memory. Virtual memory was invented in a time of scarcity (e.g., sub-MB memory) but is now deployed to a changed world with vast memory (e.g., GB to TB) where programs often don?t exploit virtual memories generality (e.g., web servers sized to not swap). At the same time, virtual memory can waste substantial execution time (on translation look aside buffer (TLB) misses) and power (accessing TLBs on each memory reference). Moreover, system extensions to support general-purpose graphics processing units (GP-GPUs) and virtual machine (VMM) challenge virtual memory more. The central hypothesis of this proposal is that memory is too virtual: most workloads do not need all of the benefits of virtual memory most of the time. To this end, we seek to de-virtualize virtual memory with multiple translation mechanisms that offer better performance with less functionality so that applications pay (performance, power/energy, space, etc.) for the features they require instead of for page-based virtual memory?s full generality always. This work reduces waste in computer systems to enable continued improvements in thier cost and performance. This improvement facilitates application innovations like higher performance for big-data workloads, including graph analysis, and environmental benefits from reduced power consumption. Beyond technical advices, this work develops and disseminates tools that leverage other NSF investments, such as the open-source ?gem5? computer-system simulation system.

该建议在虚拟内存中攻击浪费。虚拟记忆是在短缺时（例如，子MB内存）发明的，但现在已将其部署到一个变化的世界中，具有巨大的内存（例如，GB到TB），程序通常不利用虚拟记忆的通用性（例如，网络服务器（例如，大小为不交换））。同时，虚拟内存可能会浪费大量执行时间（翻译时，请旁边的缓冲区（TLB）错过）和功率（在每个内存参考上访问TLB）。此外，支持通用图形处理单元（GP-GPU）和虚拟机（VMM）的系统扩展程序更多地挑战了虚拟内存。该提案的中心假设是内存太虚拟了：大多数情况下，大多数工作负载并不需要虚拟内存的所有好处。为此，我们试图通过多种翻译机制来启用虚拟内存，这些记忆具有更好的性能，其功能较小，以便应用程序付费（性能，功率/能量，空间等），而不是用于基于页面的虚拟内存的功能，而不是基于页面的虚拟内存。这项工作减少了计算机系统中的废物，以促进其成本和性能的持续改进。这种改进促进了应用程序创新，例如用于大数据工作负载的较高性能，包括图形分析以及减少功耗所带来的环境收益。除了技术建议之外，这项工作还开发并传播了利用其他NSF投资（例如开源？GEM5）的工具？计算机系统模拟系统。