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: 2011168
• 负责人: Joseph Devietti
• 金额: $ 3万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011168&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。这些仓库里装满了数英亩的电脑，由谷歌、Facebook和亚马逊等公司运营，运行着我们每天使用的网站和应用程序。然而，尽管这些计算资源非常庞大，但它们负责运行的代码量仍然更大，并且每年以20%左右的速度增长。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应其有限的计算资源，提高数据中心程序的性能和能源效率，并减少耗电的数据中心对地球的影响。该项目将分三个阶段展开。第一阶段将利用新的硬件机制来分析程序执行，以准确了解数据中心程序在硬件级别上的运行情况。第二阶段将使用该分析信息在运行时调整程序代码，以更好地利用片上缓存。第三阶段将使用来自第一阶段的分析信息，并集成了对代码预取和代码感知缓存替换的新硬件支持，以推动缓存利用率甚至高于第二阶段。综合考虑，这些优化将加速数据中心项目并提高数据中心能源效率。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Twig: Profile-Guided BTB Prefetching for Data Center Applications

Twig：数据中心应用程序的配置文件引导 BTB 预取

• DOI: 10.1145/3466752.3480124
• 发表时间: 2021
• 期刊: 54th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO ’21
• 作者: Khan, Tanvir Ahmed;Brown, Nathan;Sriraman, Akshitha;Soundararajan, Niranjan K;Kumar, Rakesh;Devietti, Joseph;Subramoney, Sreenivas;Pokam, Gilles A;Litz, Heiner;Kasikci, Baris
• 通讯作者: Kasikci, Baris

I-SPY: Context-Driven Conditional Instruction Prefetching with Coalescing

I-SPY：使用合并的上下文驱动条件指令预取

• DOI: 10.1109/micro50266.2020.00024
• 发表时间: 2020
• 期刊: Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO
• 作者: Khan, Tanvir Ahmed;Sriraman, Akshitha;Devietti, Joseph;Pokam, Gilles;Litz, Heiner;Kasikci, Baris
• 通讯作者: Kasikci, Baris

Online Code Layout Optimizations via OCOLOS

通过 OCOLOS 在线代码布局优化

• DOI: 10.1109/mm.2023.3274758
• 发表时间: 2023
• 期刊: IEEE Micro
• 影响因子: 3.6
• 作者: Zhang, Yuxuan;Khan, Tanvir Ahmed;Pokam, Gilles;Kasikci, Baris;Litz, Heiner;Devietti, Joseph
• 通讯作者: Devietti, Joseph

OCOLOS: Online COde Layout OptimizationS

OCOLOS：在线代码布局优化

• DOI: 10.1109/micro56248.2022.00045
• 发表时间: 2022
• 期刊: International Symposium on Microarchitecture (MICRO
• 作者: Zhang, Yuxuan;Khan, Tanvir Ahmed;Pokam, Gilles;Kasikci, Baris;Litz, Heiner;Devietti, Joseph
• 通讯作者: Devietti, Joseph

Ripple: Profile-Guided Instruction Cache Replacement for Data Center Applications

• DOI: 10.1109/isca52012.2021.00063
• 发表时间: 2021-06
• 期刊: 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)
• 作者: Tanvir Ahmed Khan;Dexin Zhang;Akshitha Sriraman;Joseph Devietti;Gilles A. Pokam;Heiner Litz;Baris Kasikci