Fine-Grain Parallel Cellular Processor Arrays in 3D Silicon Technologies

Lead Research Organisation: University of Manchester
Department Name: Electrical and Electronic Engineering

Abstract

The topic of this proposal is the design of silicon microelectronic circuits that integrate thousands of simple processing cores on a single chip. In particular we will investigate circuits that integrate image sensing and image processing capabilities in a single device. These devices, sometimes called 'vision chips', perform processing using massively parallel cellular processor array architectures. High computational performance and low power consumption of such devices make them uniquely suitable for applications in embedded real-time computer vision applications such as autonomous robots, industrial machine vision, automotive security and driver assistance, interactive toys, visual prosthesis, etc. During the course of the proposed research we will develop novel vision chip circuits and architectures suitable for implementation in emerging microelectronic fabrication technologies, in particular, using 3D integrated (multi-layer stacked die) devices. We will verify our ideas via fabrication of integrated circuit prototypes and by demonstrating their computational capabilities in realistic applications.
 
Description We have developed new processor architectures, particularly suitable to applications in machine vision. We have tightly integrated arrays of simple processors and image sensors, for compact, low-power, high-performance systems. We have demonstrated working hardware prototypes of these devices, in VLSI technologies, and developed software tools that enable users to effectively program these devices. This provides foundations for using the vision chip devices in various applications.
Exploitation Route Our work has advanced the design and implementation of fine-grain processor arrays, in particular 'vision chips', based on tight integration of processing and sensing. There are opportunities for applying this technology in challenging application scenarios, especially where, small-size, low-power is important (e.g. wearable systems, autonomous robots) or high-speed (e.g. machine vision in manufacturing). We are making the current hardware prototypes and software available to interested collaborators, to be used in further research projects.
Sectors Aerospace, Defence and Marine,Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Electronics,Healthcare,Manufacturing, including Industrial Biotechology,Transport

 
Description ETH Zurich 
Organisation ETH Zurich
Country Switzerland 
Sector Academic/University 
PI Contribution We provide expertise and vision sensors hardware
Collaborator Contribution Expertise on vision algorithms, development of software
Impact Research papers on applications of vision sensors
Start Year 2015
 
Title SCAMP-5 vision chip 
Description A vision sensor integrating CMOS imager with a 256x256 processor array for ultra-fast and/or low-power machine vision applications. 
Type Of Technology Physical Model/Kit 
Year Produced 2010 
Impact Used by collaborators