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
批准号:
1438955
负责人:
Andrew Pavlo
金额:
$49.96万
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
中文摘要
要使cpu的速度超越目前的可能,还存在一些基本问题。由于单个晶体管的速度没有任何提高,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巨大的性能提升。从2GHz到10GHz)。为了克服这个问题,未来的cpu将在单个芯片上包含数百到数千个较小的计算核心,这些核心将以与当前处理器(例如2GHz)相似的速度运行。这意味着每一个核心将只和当前的cpu一样强大,但所有核心的总能力将大大超过今天的可能。这些新cpu出现的一个重要问题是,我们社会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程序的数据,包括在线业务(例如b谷歌、Facebook)、科学仪器(例如天文望远镜)和医学(例如MRI扫描仪)。它们还没有准备好处理这些新的“多核cpu”的原因是,它们大多数使用的是20世纪70年代和80年代设计的想法,当时处理器只有单核。因此,该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。该项目的结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要少。计算机架构正在向一个由多核机器主导的时代发展,一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)在设计时并没有考虑到这一点。特别是,DBMS很难有效地执行并发控制、日志记录和索引。在数百个线程并行运行的情况下,协调相互竞争的读写数据的复杂性削弱了增加核心计数的好处。因此,在本项目中,我们建议为多核时代的dbms开发一种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,在这种方法中,体系结构从一开始就设计为针对多核心系统。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在计算关键任务中的负担。欲了解更多信息,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
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批准号:1846158
-
项目类别:Continuing Grant
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资助金额:$49.41万
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财政年份:2019
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负责人:Andrew Pavlo
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依托单位:
SPX: Collaborative Research: Distributed Database Management with Logical Leases and Hardware Transactional Memory
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批准号:1822933
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项目类别:Standard Grant
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资助金额:$50.0万
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财政年份:2018
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负责人:Andrew Pavlo
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依托单位:
III: Small: Non-Invasive Real-Time Analytics in Database Systems using Holistic Query Compilation
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批准号:1718582
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项目类别:Continuing Grant
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资助金额:$49.98万
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财政年份:2017
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负责人:Andrew Pavlo
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依托单位:
III: Small: Automatic Database Management System Tuning Through Large-scale Machine Learning
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批准号:1423210
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项目类别:Standard Grant
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资助金额:$49.97万
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财政年份:2014
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负责人:Andrew Pavlo
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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
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批准号:51871067
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项目类别:面上项目
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资助金额:60.0万元
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批准年份:2018
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负责人:吴晟
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依托单位: