Collaborative Research: FoMR: Taming the Instruction Bottleneck in Modern Datacenter Applications

合作研究：FoMR：克服现代数据中心应用中的指令瓶颈

• 批准号: 2346057
• 负责人: Baris Kasikci
• 金额: $ 3万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2346057&HistoricalAwards=false
• 关键词: Collaborative; Research; FoMR; Taming; Instruction

Data centers are the power plants that drive the digital economy. These warehouses filled with acres of computers, operated by the likes of Google, Facebook and Amazon, run the websites and apps that we use every day. Yet, as vast as these computing resources are, the amount of code they are tasked with running is larger still and growing at around 20% each year. This project will explore new hardware and software mechanisms to allow large data center programs to better fit within their limited computing resources, to improve data center program performance and energy efficiency, and reduce the toll that power-hungry data centers take on our planet.This project will unfold in three stages. The first stage will leverage new hardware mechanisms for profiling program execution, to obtain an accurate picture of how a data center program is running at the hardware level. The second stage will use that profiling information to adjust the code of the program at runtime to make better use of on-chip caches. The third stage will use the profiling information from the first stage, integrated with new hardware support for code prefetching and code-aware cache replacement, to drive cache utilization even higher than in stage two. Taken together, these optimizations will accelerate data center programs and improve data center energy efficiency.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

数据中心是推动数字经济的发电厂。这些仓库里装满了英亩的计算机，由Google，Facebook和Amazon等公司运营，运行我们每天使用的网站和应用程序。然而，尽管这些计算资源是巨大的，但他们承担的跑步代码量仍然更大，并且每年以20％的速度增长。该项目将探索新的硬件和软件机制，以使大型数据中心程序更好地适合其有限的计算资源，以提高数据中心计划的性能和能源效率，并减少渴望渴望的数据中心对我们的星球造成的损失。该项目将在三个阶段中展开。第一阶段将利用新的硬件机制来分析程序执行，以获取数据中心程序如何在硬件级别运行的准确图片。第二阶段将使用该分析信息在运行时调整程序的代码，以更好地利用芯片粘贴。第三阶段将使用第一阶段的分析信息，并与新的硬件支持集成了代码预取的新硬件和代码感知的缓存更换，以使高速缓存利用率甚至比第二阶段更高。综上所述，这些优化将加速数据中心计划并提高数据中心的能源效率。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来获得支持。