CSR: SMALL: Virtualized Accelerators for Scalable, Composable Architectures

CSR：小型：用于可扩展、可组合架构的虚拟化加速器

• 批准号: 1718160
• 负责人: David Brooks
• 金额: $ 45万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718160&HistoricalAwards=false
• 关键词: CSR; SMALL; Virtualized; Accelerators; Scalable

This project seeks to develop fundamental technologies to enable the next-generation of computing devices that will power future ubiquitous computing devices such as smartphones, self-driving cars, and autonomous robots. The project develops novel tools and techniques at both the hardware and software layers of computer systems. This project will also train new graduate engineers in architecting complex computing systems, modern software and hardware design methodologies, and cutting edge machine learning techniques. All of these skillsets are in broad demand in US industry but have been underrepresented in STEM education.Heterogeneous architectures comprising general purpose processors, graphics processors, and hardware accelerators designed for specific computing tasks have been widely adopted in today's computing systems for both edge and cloud devices. Specialized computing blocks provide tremendous benefits in energy efficiency. However, a major challenge in the design of such systems is the loss of generality and flexibility that has limited their adoption to a small set of application domains that do not often change. Increased flexibility could be unlocked if accelerators were built from smaller dynamically composable blocks, but existing approaches are difficult to program and scale poorly. This project proposes a design flow to generate a templated System-on-Chip (Soc) with a composable accelerator system that can be physically instantiated for a range of computing platforms. Through a virtualization layer, collections of physical hardware blocks are exposed to software as virtual accelerators. To efficiently search the large design space of the SoC, new design space exploration techniques are under investigation.

该项目旨在开发基本技术，以实现将未来无处不在的计算设备（例如智能手机，自动驾驶汽车和自动驾驶机器人）提供动力的计算设备的下一代。该项目在计算机系统的硬件和软件层上开发了新颖的工具和技术。该项目还将在架构复杂的计算系统，现代软件和硬件设计方法以及尖端机器学习技术方面培训新的研究生工程师。所有这些技能在美国行业中的需求都广泛，但在STEM教育中的代表性不足。包括通用处理器，图形处理器以及设计用于特定计算任务的硬件加速器的均匀体系结构在当今的计算系统中广泛采用，用于边缘设备和云设备。专业计算块为能源效率提供了巨大的好处。但是，这种系统设计的主要挑战是，一般性和灵活性的丧失限制了它们对经常不变的一小部分应用程序域的采用。如果通过较小的动态组合块构建加速器，则可以解锁灵活性，但是现有方法难以编程和缩放较差。该项目提出了一个设计流，以生成具有可组合加速器系统的模板系统芯片（SOC），该系统可以在一系列计算平台上进行物理实例化。通过虚拟化层，将物理硬件块的集合作为虚拟加速器接触到软件。为了有效地搜索SOC的大型设计空间，正在研究新的设计空间探索技术。

项目成果

Trireme: Exploration of Hierarchical Multi-level Parallelism for Hardware Acceleration

• DOI: 10.1145/3580394
• 发表时间: 2023-01
• 期刊: ACM Transactions on Embedded Computing Systems
• 影响因子: 2
• 作者: Georgios Zacharopoulos;Adel Ejjeh;Ying Jing;En-Yu Yang;Tianyu Jia;I. Brumar;Jeremy Intan;Muhammad Huzaifa;S. Adve;Vikram S. Adve;Gu-Yeon Wei;D. Brooks

FlexACC: A Programmable Accelerator with Application-Specific ISA for Flexible Deep Neural Network Inference

FlexACC：具有特定于应用的 ISA 的可编程加速器，用于灵活的深度神经网络推理

• DOI: 10.1109/asap52443.2021.00046
• 发表时间: 2021
• 期刊: Architectures and Processors
• 作者: Yang, En-Yu;Jia, Tianyu;Brooks, David;Wei, Gu-Yeon
• 通讯作者: Wei, Gu-Yeon

EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference

• DOI: 10.1145/3466752.3480095
• 发表时间: 2020-11
• 期刊: MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
• 作者: Thierry Tambe;Coleman Hooper;Lillian Pentecost;Tianyu Jia;En-Yu Yang;M. Donato;Victor Sanh;P. Whatmough;Alexander M. Rush;D. Brooks;Gu-Yeon Wei

Determining Optimal Coherency Interface for Many-Accelerator SoCs Using Bayesian Optimization

• DOI: 10.1109/lca.2019.2910521
• 发表时间: 2019-07
• 期刊: IEEE Computer Architecture Letters
• 影响因子: 2.3
• 作者: K. Bhardwaj;Marton Havasi;Yuan Yao;D. Brooks;José Miguel Hernández Lobato;Gu-Yeon Wei

A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs

• DOI: 10.1145/3370748.3406564
• 发表时间: 2020-08
• 期刊: Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design
• 作者: K. Bhardwaj;Marton Havasi;Yuan Yao;D. Brooks;José Miguel Hernández-Lobato;Gu-Yeon Wei