CAREER: Overcoming the Many-Core Power Wall with Resistive Computation
CAREER: Overcoming the Many-Core Power Wall with Resistive Computation
批准号:
1054179
负责人:
Engin Ipek
金额:
$48.91万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-07-01 至 2016-06-30
中文摘要
随着晶体管数量按照摩尔-S定律呈指数级增长,功耗已成为微处理器设计中的头号问题。传统的定标理论依赖于与器件尺寸的减小成比例地降低电源电压,以控制动态功率。此外,随着电源电压的降低,漏电功率也呈指数增加。该项目提出了一种新颖的微体系结构设计技术,其目标是通过将现代微处理器的大部分功能迁移到自旋扭矩转移磁阻随机存取存储器(STT-MRAM)来避免电源墙。一种防泄漏、非易失性、阻性存储器技术。其核心思想是使用可扩展的、抗泄漏的STT-MRAM阵列和查找表来实现大多数片上存储和组合逻辑,以降低功耗,从而在固定的功率预算下允许比传统实现所能承受的更多的活跃核心。为了实现这一点,研究人员应对从基本硬件构建块的电路级实施到开发更大规模的微体系结构资源、控制策略和管理方法的所有挑战。在电路级,该项目探索了基于STT-MRAM的内容可寻址存储器、寄存器、混合单元和查找表的设计。在体系结构级别,在整个存储器层次结构中采用了新颖的高速缓存体系结构、延迟隐藏技术、吞吐量优化和写功率缓解机制。探索新颖的混合存储单元以消除大量写入队列和寄存器堆中的写入吞吐量和等待时间问题,而自适应写入策略、循环流检测器和微体系结构资源分配机制将写入功率限制为在幼稚实现下可能的一小部分。该项目还涉及基于查找表的功能单元和其他组合逻辑的设计,以及这些单元的设计和运行时重新配置。在处理器设计中利用STT-MRAM具有诱导计算机系统性能和可扩展性的显著飞跃的潜力,对整个科学、技术和社会具有巨大的积极影响。该项目预计将为高效节能多核处理器铺平道路,这种处理器可以在固定功率范围内扩展到数百个活动核心。该项目的教育部分涉及(1)对研究生和本科生进行计算机体系结构培训,(2)引入一门新的存储系统课程,将电阻记忆纳入教学大纲,以及(3)改进计算机体系结构课程,其中包括本科生的设计经验。这位调查人员计划参与当地的外联项目,促进女性和代表性不足的少数族裔参与计算机科学和工程专业,并发起一项新的努力,以增加罗切斯特大学计算机科学、电气和计算机工程专业的少数族裔入学人数。
英文摘要
As transistor count has increased exponentially with Moore?s Law, power has become the number one problem in microprocessor design. Traditional scaling theory relies on reducing supply voltages in proportion to the reduction in device dimensions to keep dynamic power in check. In addition, leakage power also increases exponentially with decreasing supply voltages. This project proposes a novel micro-architectural design technique whose goal is to avoid the power wall by migrating most of the functionality of a modern microprocessor to spin-torque transfer magneto-resistive random-access memory (STT-MRAM) ? a leakage resistant, non-volatile, resistive memory technology. The central idea is to implement most of the on-chip storage and combinational logic using scalable, leakage-resistant STT-MRAM arrays and lookup tables to lower power dissipation, thereby allowing many more active cores under a fixed power budget than a conventional implementation could afford. To accomplish this, the investigator addresses challenges all the way from the circuit-level implementation of fundamental hardware building blocks to the development of larger-scale micro-architectural resources, control policies, and management approaches. At the circuit level, the project explores the design of content-addressable memories, registers, hybrid cells, and lookup tables based on STT-MRAM. At the architecture level, novel cache architectures, latency-hiding techniques, throughput optimizations, and write-power mitigation mechanisms are employed throughout the memory hierarchy. Novel hybrid memory cells are explored to eliminate write throughput and latency problems in heavily written queues and register files, while adaptive write policies, loop stream detectors, and micro-architectural resource allocation mechanisms limit write power to a small fraction of what is possible under a naïve implementation. The project also addresses lookup-table based design of functional units and other combinational logic, as well as design- and run-time reconfiguration of these units.Leveraging STT-MRAM in processor design holds the potential to induce a significant leap in the performance and scalability of computer systems, with tremendous positive fallout to science, technology, and society at large. The project is expected to pave the way towards efficient power-aware many-core processors that can scale to hundreds of active cores under a fixed power envelope. The educational component of the project involves (1) training both graduate and undergraduate students in computer architecture, (2) the introduction of a a new memory systems course that integrates resistive memories into the syllabus, and (3) an improved computer architecture curriculum that includes design experience for undergraduates. The investigator plans involvement in local outreach programs promoting the participation of women and underrepresented minorities in computer science and engineering, and initiating a new effort to increase the enrollment of minorities in University of Rochester's computer science and electrical and computer engineering programs.
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XPS: EXPL: DSD: A Memristive Hardware Platform for Large Scale Combinatorial Optimization
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批准号:1533762
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项目类别:Standard Grant
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资助金额:$29.83万
-
财政年份:2015
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负责人:Engin Ipek
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依托单位:
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项目类别:Standard Grant
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资助金额:$9.37万
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财政年份:2015
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依托单位:
Application-Specific Memory System Optimizations using Programmable Memory Controllers
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批准号:1217418
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项目类别:Standard Grant
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资助金额:$30.0万
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财政年份:2012
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负责人:Engin Ipek
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依托单位:
海外基金