CSR: Medium: Energy-Efficient Architectures for Emerging Big-Data Workloads

CSR：中：新兴大数据工作负载的节能架构

• 批准号: 1302663
• 负责人: Rajeev Balasubramonian
• 金额: $ 87.33万
• 依托单位: University of Utah
• 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: 2013-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1302663&HistoricalAwards=false
• 关键词: CSR; Medium; Energy; Efficient; Architectures

In modern server architectures, the processor socket and the memory systemare implemented as separate modules. Data exchange between these modulesis expensive -- it is slow, it consumes a large amount of energy, and thereare long wait times for narrow data links. Emerging big-data workloads willrequire especially large amounts of data movement between the processorand memory. To reduce the cost of data movement for big-data workloads,the project attempts to design new server architectures that can leverage3D stacking technology. The proposed approach, referred to as Near DataComputing (NDC), reduces the distance between a subset of computationalunits and a subset of memory, and can yield high efficiency for workloadsthat exhibit locality. The project will also develop new big-data algorithms and runtime systems that can exploit the properties of thenew architectures.The project will lead to technologies that can boost performance andreduce the energy demands of big-data workloads. Several reports havecited the importance of these workloads to national, industrial, andscientific computing infrastructures. The project outcomes will beintegrated into University of Utah curricula and will play a significantrole in a new degree program on datacenter design and operation. ThePIs will broaden their impact by publicly distributing parts of theirsoftware infrastructure and by engaging in outreach programs thatinvolve minorities and K-12 students.

在现代服务器架构中，处理器插槽和存储器系统被实现为单独的模块。 这些模块之间的数据交换是昂贵的-它是缓慢的，它消耗大量的能源，并有很长的等待时间狭窄的数据链路。 新兴的大数据工作负载将需要在处理器和内存之间进行特别大量的数据移动。 为了降低大数据工作负载的数据移动成本，该项目尝试设计能够支持3D堆栈技术的新服务器架构。 所提出的方法，被称为近数据计算（NDC），减少了计算单元的子集和内存的子集之间的距离，并可以产生高效率的工作负载，表现出局部性。 该项目还将开发新的大数据算法和运行时系统，以利用新架构的特性。该项目将导致能够提高性能和降低大数据工作负载的能源需求的技术。 一些报告已经指出了这些工作负载对国家、工业和科学计算基础设施的重要性。 该项目的成果将被整合到犹他州大学的课程中，并将在数据中心设计和运营的新学位课程中发挥重要作用。 PI将通过公开分发部分软件基础设施和参与涉及少数民族和K-12学生的外展计划来扩大其影响。