Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform

合作研究：FuSe：R3AP：可重调、可重新配置、赛道内存加速平台

• 批准号: 2328973
• 负责人: Qi Zhu
• 金额: $ 25万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328973&HistoricalAwards=false
• 关键词: Collaborative; Research; FuSe; R3AP; Retunable

In traditional Von Neumann computing systems, a significant bottleneck arises because the data transfer speed to and from the computing units has considerably fallen behind capacity, processing speed, and efficiency. To mitigate this bottleneck by bridging the gap between storage and computation, many innovative storage technologies have been introduced, along with near- and in-memory processing solutions designed for both emerging and traditional memory systems. Nonetheless, a considerable challenge remains: the prototyping and characterization of actual fabricated systems, especially those encompassing both mature technologies and cutting-edge technologies. To overcome this challenge, this project develops a cutting-edge Retunable and Reconfigurable Acceleration Platform (R3AP) based on emerging racetrack memory, leveraging a device-architecture-application co-design approach. The standout features of R3AP include its ability to function as a reconfigurable logic, a processing-in-memory (PIM) accelerator, and a high-density memory storage. It is retunable, meaning it can operate with bit-wise, integer, and floating-point precision, and can simulate analog-like storage and processing. R3AP effectively mitigates data movement inefficiencies while offering domain-specific acceleration and adaptability. With its dense, reliable, energy-efficient, and ultra-low latency computational capability, R3AP has the potential to revolutionize the storage and processing capabilities of future computing systems, such as those in Internet of Things (IoT) and Cyber-Physical Systems (CPS). It can also be applied to high-performance and cloud computing systems. The project's findings are shared through publications, workshops, design contests, tutorials, industrial courses, and technology transfer activities. Educational resources and outreach activity plans are made available on the project website, and software artifacts are released on GitHub.To realize R3AP, the project comprises a series of interrelated research tasks spanning multiple system layers. At the device level, the project integrates the voltage-controlled skyrmion motion mechanism with the industrial-grade 8-inch wafer magnetic tunneling junction stack and demonstrates a fully functional Skyrmion racetrack memory (SRTM), including the formation, shifting, and detection of the skyrmion stream. Additionally, it evaluates the performance of SRTM, focusing on aspects such as write-error-rate, shift-error-rate, read-error-rate, operation speed, and energy consumption. It also addresses and mitigates non-idealities, such as the pinning effect, and goes on to develop and demonstrate CMOS-integrated SRTM. On the architecture and circuit layers, the project involves the creation of a mutable lookup table, compute, and memory unit. This unit performs like multi-context Field-Programmable Gate Array (FPGA) logic, parallel PIM logic, massively parallel accumulators, and analog-like storage and compute structures, leveraging the unique properties of SRTM. This layer ensures high-speed memory access from a hierarchy consisting of banks, subarrays, tiles, etc., and further adds links via configurable switch boxes and a mesh-based network-on-chip to enable data movement operations for PIM that would otherwise be challenging. At the application layer, the project develops novel modeling, analysis, design space exploration, and runtime adjustment techniques to exploit the high degree of reconfigurability provided by R3AP. The goal is to adapt future IoT and CPS applications to changing environments and requirements, optimize resource usage, withstand external disturbances, and enhance overall system performance, resilience, and sustainability. Across all these layers, the project develops a scalable computer-aided design (CAD) flow. This involves a multi-level intermediate representation-based compilation flow, which can compile high-level description languages such as PyTorch and C/C++ into binaries for the R3AP device. This flow uses a multi-level hierarchy including front-end, middle-end, and back-end compilation of the designs, and abstracts various optimization and management problems to a suitable level for efficient resolution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在传统的von Neumann计算系统中，出现了一个重要的瓶颈，因为往返计算单元的数据传输速度已大大落后于容量，处理速度和效率。为了通过弥合存储和计算之间的差距来减轻这种瓶颈，已经引入了许多创新的存储技术，以及为新兴和传统存储系统设计的近乎内存和内存的处理解决方案。但是，仍然存在一个巨大的挑战：实际制造系统的原型和表征，尤其是那些涵盖成熟技术和尖端技术的系统。为了克服这一挑战，该项目基于新兴的赛车记忆，开发了一个可恢复和可重新配置的加速平台（R3AP），利用设备 - 架构 - 应用程序应用共同设计方法。 R3AP的出色功能包括其作为可重构逻辑的功能，内存处理（PIM）加速器以及高密度存储器存储的能力。它是可重新渗透的，这意味着它可以以刻度，整数和浮点精度运行，并可以模拟类似模拟的存储和处理。 R3AP有效地减轻了效率低下的数据运动，同时提供了特定于域的加速度和适应性。 R3AP凭借其密集，可靠，节能和超低潜伏期计算能力，有可能彻底改变未来计算系统的存储和处理能力，例如物联网（IoT）和网络物理系统（CPS）。它也可以应用于高性能和云计算系统。该项目的发现是通过出版物，研讨会，设计竞赛，教程，工业课程和技术转移活动共享的。在项目网站上提供了教育资源和外展活动计划，并且在GitHub上发布了软件工件。为了实现R3AP，该项目包括一系列相互关联的研究任务，这些任务涵盖了多个系统层。在设备级别上，该项目将电压控制的天空运动机构与工业级的8英寸晶圆磁性隧道接线堆栈进行了整合，并展示了功能齐全的Skyrmion Racetrack Memory（SRTM），包括Skyrmion流的形成，移动和检测。此外，它评估了SRTM的性能，重点是诸如写入误差，转移率速率，读取率率，操作速度和能耗等方面。它还解决并缓解非理想性，例如固定效应，并继续开发和演示CMOS集成的SRTM。在体系结构和电路层上，该项目涉及创建可变的查找表，计算和内存单元。该单元执行的执行诸如多字段可编程的门阵列（FPGA）逻辑，并行PIM逻辑，大量并行累加器以及类似类似的存储和计算结构，利用SRTM的唯一属性。该层可确保从由银行，子阵列，瓷砖等组成的层次结构进行的高速内存访问，并通过可配置的开关框和基于网格的网络芯片添加链接，以启用PIM的数据移动操作，否则这将是具有挑战性的。在应用层，该项目开发了新颖的建模，分析，设计空间探索和运行时调整技术，以利用R3AP提供的高度重构性。目的是将未来的物联网和CPS应用程序调整到不断变化的环境和需求中，优化资源使用，承受外部干扰，并增强整体系统性能，弹性和可持续性。在所有这些层中，该项目开发了可扩展的计算机辅助设计（CAD）流。这涉及基于多级中间表示的汇编流，该流程可以将高级描述语言（例如Pytorch和C/C ++）编译成R3AP设备的二进制文件。该流程使用了多层层次结构，包括设计设计的前端，中端和后端汇编，并摘要各种优化和管理问题，以适合有效解决的水平。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子和更广泛的影响来评估的支持，并被认为是值得的。