SHF: Small: Collaborative Research: Power-Efficient and Reliable 3D Stacked Reconfigurable Photonic Network-on-Chips for Scalable Multicore Architectures
SHF:小型:协作研究:用于可扩展多核架构的高效且可靠的 3D 堆叠可重构光子片上网络
基本信息
- 批准号:1547034
- 负责人:
- 金额:$ 30.87万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-05-15 至 2019-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
As power dissipation on a single-chip is increasing at an alarming rate due to massive integration of digital circuits, multicore design has become the only technique to scale performance. Multicores with tens to hundreds of cores are already available in the marketplace and future projections call for thousands of cores on the chip. To achieve scalable computing performance from the multicores, the communication between cores should also scale in bandwidth while significantly reducing the power consumption. Scaling the performance of the on-chip communication fabric, called the Network-on-Chip (NoC), has proven to be a significant challenge with traditional metallic interconnects due to fundamental signaling issues such as power dissipation, electromagnetic interference, crosstalk and reflections. Several studies and roadmaps have indicated that disruptive technology solutions such as photonics have the potential to alleviate the critical bandwidth, power and latency challenges of future multicores. This research seeks to exploit the unique advantages of photonic interconnects and 3D stacking technologies to develop scalable, energy-efficient, bandwidth-reconfigurable and reliable NoCs for future multicores. There are three goals of the proposed research; first, it will investigate and develop 3D stacked photonic NoC architectures and topologies that maximize performance and improve energy-efficiency. Second, it will develop runtime reconfiguration techniques that can adapt the network to the communication needs of the application, thereby improving performance on a per-application basis. Third, it will result in an extensive modeling and simulation framework to be used for designing and validating future photonic NoC architectures.This research has far reaching broader impacts. This research is uniquely positioned to leverage two emerging technologies namely photonics and 3D stacking to meet the multicore challenge and will significantly benefit society. The proposed research is essential to continue the growth of computing performance that our society depends upon, and will result in digital devices ranging from smartphones to laptops with faster response time and improved reliability. By investigating the design of energy-efficient and high-bandwidth photonic-3D NoC architectures, this proposal describes a transformative and viable approach to combine technology, algorithm and applications? research to enable building scalable multicores. The cross-cutting nature of this research will foster new research directions in several areas, spanning technology/energy-aware NoC design, novel computer architectures, and cutting-edge modeling and simulations tools for emerging technologies. This research will also play a major role in education by integrating discovery with teaching and training. Several graduate students will be directly involved with all phases of the project from which the core parts of their dissertations and theses will be derived. It will also benefit a wider audience of graduate and undergraduate students by incorporating the new research into several courses on computer architecture and parallel processing taught by the PIs. Finally, the results and findings of the proposed research will be disseminated to researchers, engineers and educators through technical publications and presentations.
由于数字电路的大规模集成,单芯片上的功耗正以惊人的速度增加,多核设计已成为扩展性能的唯一技术。市场上已经有数十到数百个核心的多核,未来的预测需要芯片上有数千个核心。为了通过多核实现可扩展的计算性能,核之间的通信还应该扩展带宽,同时显着降低功耗。由于功耗、电磁干扰、串扰和反射等基本信号问题,扩展片上通信结构(称为片上网络 (NoC))的性能已被证明是传统金属互连的一项重大挑战。多项研究和路线图表明,光子学等颠覆性技术解决方案有可能缓解未来多核的关键带宽、功耗和延迟挑战。这项研究旨在利用光子互连和 3D 堆叠技术的独特优势,为未来的多核开发可扩展、节能、带宽可重新配置且可靠的 NoC。拟议研究的三个目标;首先,它将研究和开发 3D 堆叠光子 NoC 架构和拓扑,以最大限度地提高性能并提高能源效率。其次,它将开发运行时重新配置技术,使网络适应应用程序的通信需求,从而提高每个应用程序的性能。第三,它将产生一个广泛的建模和仿真框架,用于设计和验证未来的光子 NoC 架构。这项研究具有更广泛的影响。这项研究具有独特的优势,利用光子学和 3D 堆叠这两种新兴技术来应对多核挑战,并将显着造福社会。拟议的研究对于继续提高我们社会所依赖的计算性能至关重要,并将带来从智能手机到笔记本电脑等数字设备的更快响应时间和更高的可靠性。通过研究节能和高带宽光子 3D NoC 架构的设计,该提案描述了一种将技术、算法和应用相结合的变革性且可行的方法?研究以构建可扩展的多核。这项研究的跨领域性质将在多个领域培育新的研究方向,涵盖技术/能源感知 NoC 设计、新颖的计算机架构以及新兴技术的尖端建模和仿真工具。这项研究还将发现与教学和培训相结合,在教育中发挥重要作用。一些研究生将直接参与该项目的所有阶段,他们的论文和论文的核心部分将从中衍生出来。通过将新研究纳入 PI 教授的计算机体系结构和并行处理的几门课程中,它还将使更广泛的研究生和本科生受益。最后,拟议研究的结果和发现将通过技术出版物和演示文稿传播给研究人员、工程师和教育工作者。
项目成果
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Ahmed Louri其他文献
Nanoscale Accelerators for Artificial Neural Networks
人工神经网络纳米级加速器
- DOI:
10.1109/mnano.2022.3208757 - 发表时间:
2022-12-01 - 期刊:
- 影响因子:1.6
- 作者:
Farzad Niknia;Ziheng Wang;Shanshan Liu;Ahmed Louri;Fabrizio Lombardi - 通讯作者:
Fabrizio Lombardi
Ahmed Louri的其他文献
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{{ truncateString('Ahmed Louri', 18)}}的其他基金
Collaborative Research: SHF: Medium: EPIC: Exploiting Photonic Interconnects for Resilient Data Communication and Acceleration in Energy-Efficient Chiplet-based Architectures
合作研究:SHF:中:EPIC:利用光子互连实现基于节能 Chiplet 的架构中的弹性数据通信和加速
- 批准号:
2311543 - 财政年份:2023
- 资助金额:
$ 30.87万 - 项目类别:
Continuing Grant
Collaborative Research: DESC: Type II: Multi-Function Cross-Layer Electro-Optic Fabrics for Reliable and Sustainable Computing Systems
合作研究:DESC:II 型:用于可靠和可持续计算系统的多功能跨层电光织物
- 批准号:
2324644 - 财政年份:2023
- 资助金额:
$ 30.87万 - 项目类别:
Standard Grant
Collaborative Research: CSR: Small: Cross-layer learning-based Energy-Efficient and Resilient NoC design for Multicore Systems
协作研究:CSR:小型:基于跨层学习的多核系统节能和弹性 NoC 设计
- 批准号:
2321224 - 财政年份:2023
- 资助金额:
$ 30.87万 - 项目类别:
Standard Grant
SHF: Small: Holistic Design of High-performance and Energy-efficient Accelerators for Graph Neural Networks
SHF:小型:图神经网络高性能、高能效加速器的整体设计
- 批准号:
2131946 - 财政年份:2021
- 资助金额:
$ 30.87万 - 项目类别:
Standard Grant
Collaborative Research: SHF: Medium: Neural-Network-based Stochastic Computing Architectures with applications to Machine Learning
合作研究:SHF:中:基于神经网络的随机计算架构及其在机器学习中的应用
- 批准号:
1953980 - 财政年份:2020
- 资助金额:
$ 30.87万 - 项目类别:
Continuing Grant
SHF: Medium: Collaborative Research: Photonic Neural Network Accelerators for Energy-efficient Heterogeneous Multicore Architectures
SHF:媒介:协作研究:用于节能异构多核架构的光子神经网络加速器
- 批准号:
1901165 - 财政年份:2019
- 资助金额:
$ 30.87万 - 项目类别:
Continuing Grant
SHF: Small: Collaborative Research: Integrated Framework for System-Level Approximate Computing
SHF:小型:协作研究:系统级近似计算的集成框架
- 批准号:
1812495 - 财政年份:2018
- 资助金额:
$ 30.87万 - 项目类别:
Standard Grant
SHF: Medium: Collaborative Research: Machine Learning Enabled Network-on-Chip Architectures Optimized for Energy, Performance and Reliability
SHF:中:协作研究:支持机器学习的片上网络架构,针对能源、性能和可靠性进行了优化
- 批准号:
1702980 - 财政年份:2017
- 资助金额:
$ 30.87万 - 项目类别:
Continuing Grant
SHF: Medium: Collaborative Research: Scaling On-chip Networks to 1000-core Systems using Heterogeneous Emerging Interconnect Technologies
SHF:中:协作研究:使用异构新兴互连技术将片上网络扩展到 1000 核系统
- 批准号:
1513923 - 财政年份:2015
- 资助金额:
$ 30.87万 - 项目类别:
Continuing Grant
SHF: Small: Collaborative Research: A Holistic Design Methodology for Fault-Tolerant and Robust Network-on-Chips (NoCs) Architectures
SHF:小型:协作研究:容错和鲁棒片上网络 (NoC) 架构的整体设计方法
- 批准号:
1547035 - 财政年份:2015
- 资助金额:
$ 30.87万 - 项目类别:
Standard Grant
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