COLLABORATIVE RESEARCH: RECONFIGURABLE COMPUTING USING 2D NANOSCALE MEMORY ARRAY FOR MULTIMEDIA SIGNAL PROCESSING

Swarup Bhunia，凯斯西储大学saibal Mukhopadhyay，佐治亚理工学院合作研究：基于二维纳米级存储阵列的多媒体信号处理可重构计算这个合作研究项目探索了一个可扩展的可重构计算平台，用于多媒体信号处理（MSP）应用，使用集成的二维易失性或非易失性存储器阵列作为主要计算元素。该平台被称为基于内存的多媒体信号处理（MBMSP），它利用了纳米级硅以及许多新兴纳米级器件的规则和周期性结构都适合高密度、高性能存储器设计的事实。在MBMSP中，算法任务在功能上被分解为多输入、多输出函数，然后将其映射为内存数组中的查找表，并使用小型控制器以时间复用的拓扑方式进行评估。这种完全不同的信息处理方法可以有效地开发具有高性能、可重构性、能效和可靠性的可扩展平台，用于各种复杂的信号处理系统。该研究旨在为MBMSP开发电路-微架构-软件协同设计方法，包括软件架构，以提高性能和可扩展性；存储单元和阵列的电路微架构技术，实现低功耗和鲁棒性；能源与可靠性软硬件协同设计方法以及一个基于自旋扭矩传输随机存取存储器（strtram）的平台，用于将MBMSP扩展到深度纳米节点。更广泛的影响：MBMSP平台可以潜在地改变传统的多媒体信号处理系统的设计方法。该研究将通过课程模块开发和本科研究项目整合教育。这些教学模块将适用于当地的高中生，其中包括每年夏天参加凯斯西储大学大学预科课程的约40%的少数族裔/弱势学生。这些模块将侧重于多媒体/数字信号处理系统的实践学习方法和设计它们的新方法。pi将继续参与促进非裔美国人在工程和科学方面的学术生涯（FACES）和少数民族暑期本科生研究经验（SURE）。pi每年夏天将指导一名SURE学生，并让他们参与拟议的研究。

Lead Proposal ECCS-1002237 Swarup Bhunia, Case Western Reserve UniversityNon-Lead Proposal ECCS-1002090Saibal Mukhopadhyay, Georgia Institute of TechnologyCollaborative Research: Reconfigurable Computing Using 2D Nanoscale Memory Array for Multimedia Signal ProcessingABSTRACTIntellectual Merit: This collaborative research project explores a scalable reconfigurable computing platform for Multimedia Signal Processing (MSP) applications using integrated two-dimensional volatile or non-volatile memory array as the primary computing element. The platform, referred to as Memory Based Multimedia Signal Processing (MBMSP), leverages on the fact that both nanoscale silicon as well as regular and periodic structures of many emerging nanoscale devices are amenable to dense, high-performance memory design. In MBMSP, algorithmic tasks are functionally decomposed into multi-input, multi-output functions, which are then mapped as lookup tables in a memory array and evaluated in a time-multiplexed, topological fashion using a small controller. This fundamentally different approach to information processing can be effective in developing a scalable platform with high-performance, reconfigurability, energy-efficiency and reliability for diverse and complex signal processing systems. The research seeks to develop circuit-µ-architecture-software co-design approach for MBMSP including software architecture to improve performance and scalability; circuit-µ-architecture techniques for memory cell and array to achieve low-power and robustness; software-hardware co-design approach for energy and reliability; and a Spin-Torque-Transfer Random Access Memory (STTRAM) based platform for scaling MBMSP to deep nanometer nodes.Broader Impacts: The MBMSP platform can potentially transform the traditional approach to design multimedia signal processing system. The research will integrate education through course module development and undergraduate research projects. The teaching modules will be adapted for the local high-school students, including about 40% minority/under-represented students, who join the pre-college program at Case Western Reserve University every summer. The modules will focus on hands-on learning approaches for multimedia/digital signal processing systems and new ways to design them. PIs will continue their involvement with Facilitating Academic Careers in Engineering and Science for African-American (FACES) and Summer Undergraduate Research Experience for minorities (SURE). PIs will mentor one SURE student every summer and involve them in the proposed research.