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XPS: FULL: DSD: Collaborative Research: Moving the Abyss: Database Management on Future 1000-core Processors

XPS: FULL: DSD: Collaborative Research: Moving the Abyss: Database Management on Future 1000-core Processors
XPS:完整:DSD:协作研究:移动深渊:未来 1000 核处理器上的数据库管理
批准号:
1438955
负责人:
Andrew Pavlo
金额:
$49.96万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2018-08-31

项目摘要

项目成果

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中文摘要
翻译
有一些根本性的问题,以加快CPU超越什么是今天的可能。由于单个晶体管不会变得更快,像英特尔和AMD这样的制造商不再能够仅仅通过提高时钟速度来获得大规模的性能改进(例如,从2GHz到10GHz)。为了克服这一点,未来的CPU将在一个芯片上包含数百到数千个较小的计算核心,这些核心都将以类似于当前处理器的速度运行(例如,2GHz)。这意味着每个内核的功能将与当前的CPU一样强大,但所有内核的总功率将远远超过今天的可能性。这些新CPU出现的一个重要问题是,在我们社会的各个方面使用的数据库系统不适合这种变化。这样的数据库系统用于存储和访问各种应用的数据,包括在线商务(例如,Google、Facebook)、科学仪器(例如,天文望远镜),和医学(例如,MRI扫描仪)。他们还没有准备好处理这些新的“多核CPU”的原因是因为他们中的大多数使用的是20世纪70年代和80年代设计的想法,当时处理器只有一个内核。因此,本项目的目的是开发软件和硬件技术,使数据库系统能够利用未来CPU架构的全部计算能力。该项目的成果将使组织能够在更少的机器上部署未来的应用程序,这些机器使用的能源比目前使用的更少。计算机体系结构正在走向一个由单核机器主导的时代,单个芯片上有数百个核心。这种前所未有的片上并行性为可伸缩性引入了一个新的维度,而当前的数据库管理系统(DBMS)并不是为这个维度而设计的。特别是,DBMS要有效地执行并发控制、日志记录和索引变得非常困难。由于有数百个线程并行运行,协调对数据的竞争性读和写的复杂性降低了增加核心数量的好处。因此,在本项目中,我们提出了一种面向众核时代的数据库管理系统的软硬件协同设计方法。在软件方面,PI不是试图通过增量改进来消除现有DBMS体系结构的可伸缩性瓶颈,而是寻求一种自底向上的方法,即体系结构从一开始就针对多核系统。在硬件方面,PI将设计新的硬件组件,而不是简单地在单个芯片上添加更多的内核,这些硬件组件可以减轻软件系统的计算关键任务。有关详细信息,请参阅项目网站:http://db.cs.cmu.edu/projects/1000cores/
英文摘要
There are fundamental problems to speeding up CPUs beyond what ispossible today. Because individual transistors are not getting anyfaster, manufacturers like Intel and AMD are no longer able to getmassive performance improvements just by increasing clock speeds(e.g., going from 2GHz to 10GHz). To overcome this, future CPUs willcontain hundreds to thousands of smaller computational cores on asingle chip which will all run at the speed similar to currentprocessors (e.g., 2GHz). This means that each single core will only beas powerful as current CPUs, but that the total aggregate power of allthe cores will be significantly more than what is possible today. Animportant problem with the advent of these new CPUs is that thedatabase systems that are used in all aspects of our society areill-suited for this change. Such database systems are used to storeand access data for a variety of applications, including on-linebusiness (e.g., Google, Facebook), scientific instruments (e.g.,astronomical telescopes), and medicine (e.g., MRI scanners). Thereason that they are not ready to handle these new "many-core CPUs" isbecause most of them use ideas that were designed in the 1970s and1980s when processors only had a single core. Thus, the purpose ofthis project is to develop both software and hardware technologiesthat will allow database systems to utilize the full computationalpower of future CPU architectures. The results of this project willenable organizations to deploy future applications on fewer machinesthat use less energy than what is currently used today.Computer architectures are moving towards an era dominated bymany-core machines with hundreds of cores on a single chip. Thisunprecedented level of on-chip parallelism introduces a new dimensionto scalability that current database management systems (DBMSs) werenot designed for. In particular, it becomes exceedingly difficult forthe DBMS to perform concurrency control, logging, and indexingefficiently. With hundreds of threads running in parallel, thecomplexity of coordinating competing reads and writes to datadiminishes the benefits of increased core counts. Thus, in thisproject we propose to develop a software-hardware co-design approachfor DBMSs in the many-core era. On the software side, rather thanattempting to remove scalability bottlenecks of existing DBMSarchitectures through incremental improvements, the PIs seek a bottom-upapproach where the architecture is designed to target many-coresystems from inception. On the hardware side, instead of simply addingmore cores to a single chip, the PIs will design new hardware componentsthat can unburden the software system from computationally criticaltasks.For further information see project web site at:http://db.cs.cmu.edu/projects/1000cores/
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CAREER: Self-Driving Database Management Systems
  • 批准号:
    1846158
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.41万
  • 财政年份:
    2019
  • 负责人:
    Andrew Pavlo
  • 依托单位:
SPX: Collaborative Research: Distributed Database Management with Logical Leases and Hardware Transactional Memory
  • 批准号:
    1822933
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2018
  • 负责人:
    Andrew Pavlo
  • 依托单位:
III: Small: Non-Invasive Real-Time Analytics in Database Systems using Holistic Query Compilation
  • 批准号:
    1718582
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.98万
  • 财政年份:
    2017
  • 负责人:
    Andrew Pavlo
  • 依托单位:
III: Small: Automatic Database Management System Tuning Through Large-scale Machine Learning
  • 批准号:
    1423210
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.97万
  • 财政年份:
    2014
  • 负责人:
    Andrew Pavlo
  • 依托单位:
国内基金
海外基金
钴基Full-Heusler合金的掺杂效应和薄膜噪声特性研究
  • 批准号:
    51871067
  • 项目类别:
    面上项目
  • 资助金额:
    60.0万元
  • 批准年份:
    2018
  • 负责人:
    吴晟
  • 依托单位: