Configurable 3D-integrated focal-plane sensor-processor array architecture

A mixed-signal Cellular Visual Microprocessor architecture with digital processors is described. An ASIC implementation is also demonstrated. The architecture is composed of a regular sensor readout circuit array, prepared for 3D face-to-face type integration, and one or several cascaded array of mainly identical (SIMD) processing elements. The individual array elements derived from the same general HDL description and could be of different in size, aspect ratio, and computing resources

Digital processor array implementation aspects of a 3D multi-layer vision architecture

Trabajo presentado al 12th CNNA celebrado en Berkeley (USA) del 3 al 5 de febrero de 2010.Technological aspects of the 3D integration of a multilayer combined mixed-signal and digital sensor-processor array chip is described. The 3D integration raises the question of signal routing, power distribution, and heat dissipation, which aspects are considered systematically in the digital processor array layer as part of the multi layer structure. We have developed a linear programming based evaluation system to identify the proper architecture and its parameters.The work is supported by the Eutecus ONR-BAA Co. Num N00173-08-C-4005 VISCUBE project.Peer Reviewe

3D multi-layer vision architecture for surveillance and reconnaissance applications

The architecture and the design details of a multilayer combined mixed-signal and digital sensor-processor array chip is shown. The processor layers are fabricated with 3D integration technology, and the sensor layer is integrated via bump bonding technology. The chip is constructed of a 320 x 240 sensor array layer, closely coupled with a 160 x 120 mixed-signal processor array layer, a digital frame buffer layer, and an 8 x 8 digital fovea processor array layer. The chip is designed to solve image registration and feature extraction above 1000FPS.Office of Naval Research (USA) N00173-08-C-400

Exploration of spatial-temporal dynamic phenomena in a 32×32-cell stored program two-layer CNN universal machine chip prototype

This paper describes a full-custom mixed-signal chip that embeds digitally programmable analog parallel processing and distributed image memory on a common silicon substrate. The chip was designed and fabricated in a standard 0.5 μm CMOS technology and contains approximately 500 000 transistors. It consists of 1024 processing units arranged into a 32 × 32 grid. Each processing element contains two coupled CNN cores, thus, constituting two parallel layers of 32 × 32 nodes. The functional features of the chip are in accordance with the 2nd Order Complex Cell CNN-UM architecture. It is composed of two CNN layers with programmable inter- and intra-layer connections between cells. Other features are: cellular, spatial-invariant array architecture; randomly selectable memory of instructions; random storage and retrieval of intermediate images. The chip is capable of completing algorithmic image processing tasks controlled by the user-selected stored instructions. The internal analog circuitry is designed to operate with 7-bits equivalent accuracy. The physical implementation of a CNN containing second order cells allows real-time experiments of complex dynamics and active wave phenomena. Such well-known phenomena from the reaction-diffusion equations are traveling waves, autowaves, and spiral-waves. All of these active waves are demonstrated on-chip. Moreover this chip was specifically designed to be suitable for the computation of biologically inspired retina models. These computational experiments have been carried out in a developmental environment designed for testing and programming the analogic (analog-and-logic) programmable array processors.Hungarian Academy of Sciences SIVA-2Comisión Interministerial de Ciencia y Tecnología TICC99-0826Office of Naval Research (USA) N00014-00-1-042

A Bio-Inspired Two-Layer Mixed-Signal Flexible Programmable Chip for Early Vision

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.Office of Naval Research (USA) N-000140210884European Commission IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

Érzékelő-értelmező topografikus számítógépek - természet motiválta architektúrák és elektronikai implementációk (multidiszciplináris tudományos iskola) = Sensing-understanding topographic computers - bioinspired architectures and electronic implementations

A tervezett multidiszciplináris kutatómunka a jelzett időszakban sok új elemmel bővült és az eredeti célkitűzéseken túl ma átfogja a következő tematikai elemeket: - a celluláris érzékelő hullám-számitógép architektúrák széles körét - a nanotechnológia, a mikroelektronika (beleértve a MEMS) és az optoelektronika területeit, - a nano-bio technológia és molekuláris biológia kapcsolódó elemeit, - a neurobiológiai (''konstrukciók'') funkcionális elemzését, - a multimodális érzékelésen és ennek elemzésén keresztül a szemantikus beágyazást és - a humán nyelvtechnológia új irányzatait. Az eredmények közül kiemeljük a celluláris vizuális mikroprocesszorral végzett munkákra vonatkozóakat a sokcsatornás emlős retina modellezés, az echokardiogáfiás diagnózis, immune válasz inspirálta sok célpontos azonositás, optikai folyam számitás, a többcélpontos elemzés és követés, valamint a multimodális fűzió és a téridőbeli kaotikus attraktorok azonositása területén. A nanoantennák terbezése, valamint a siketek mobiltelefonja és a humán nyelvtechnológia , továbbú a tapintás érzékelés terén is jelentős eredmények születtek. | The main fields of the doctoral school are as follows: - cellular wave-computer architectures - nanotechnology, microelectronics (including MEMS) and optoelectronics - nano-bio technology and related fields of molecular biology - neuromorphic functional modelling of some parts of the sensory organs and systems - multimodal sensing and fusion including the semantic embedding - key aspects and algorithms of human language technology The following results are some highlights among the main results, namely, the neuromorphic multichannel modeling of the mammalian retina, diagnostic tools for echocardiography, immune response inspired many-target identification, optical flow calculation, multitarget identification and tracking, multimodal fusion, spatial-temporal chaotic attractor identification. Important results were published in the fields on nano-antenna design, algorithms for mobile phone use for deaf people, and some key algorithms of human language technology

Receptive field atlas and related CNN models

In this paper we demonstrate the potential of the cellular nonlinear/neural network paradigm (CNN) that of the analogic cellular computer architecture (called CNN Universal Machine | CNN-UM) in modeling different parts and aspects of the nervous system. The structure of the living sensory systems and the CNN share a lot of features in common: local interconnections ("receptive field architecture"), nonlinear and delayed synapses for the processing tasks, the potentiality of feedback and using the advantages of both the analog and logic signal-processing mode. The results of more than ten years of cooperative work of many engineers and neurobiologists have been collected in an atlas: what we present here is a kind of selection from these studies emphasizing the exibility of the CNN computing: visual, tactile and auditory modalities are concerned

Info-Bionika, Nanoelektronika és Mesterséges értés - Multidiszciplináris Információs Technológia = Info-Bionics, Nanoelectronics and Artificial Understanding - Multidisciplinary Information Technology

A Multidiszciplináris Doktori Iskolánk három tudományága: az informatikai tudományok, a villamosmérnöki tudományok és a biológiai tudományok. Az utóbbi két évben tízen szereztek fokozatot és a doktori iskola létszáma közel 50 főre nőtt. Néhány konkrét kiemelendő eredmény a következő: - Celluláris hullám számítógép chip-en logikai, analóg és a zaj jelek algoritmikus keverése, pl. valódi véletlen bit térképek generálása - Navier-Stokes és geotermikus PDE megoldó Celluláris Multiprocesszoros gépek kidolgozása - Audio események detektálása Celluláris algoritmusokkal - Celluláris hullám algoritmusok sok mozgó tárgy követésére, mesterséges immunrendszer algoritmusokat - Részvétel nano-antenna elemek tervezésében - Molekuláris dinamika modellezése szuper számítógépen - Feltűnőségi modellek a látásban, emberi teszt-kísérletekkel - Agyi bionikus interfész elektróda MEMS kivitelben - CMOS technológián részegységek tervezése, hiperpontosság az időben - 3 Dimenziós tapintó mérő eszköz és szoftver ? Siketek mobiltelefonjához szájmozgás animáció - Bénult végtagú gerincsérültek lábmozgatása bionikus, nem invazív úton - Új nyelvtechnológiai eszközök magyar és angol szövegelemzéshez és fordítástámogatáshoz Fontos eredmény egy olyan doktorandusi közösség létrehozása, amelyben a multidiszciplináris gondolkodásmód természetessé válik. A publikációkon túl - számuk a beszámolási időszakban mintegy 100 - évente a szakmai beszámolókat nyilvánosan meghirdettük és egy-egy színes kötetben megjelentettük. | The Doctoral School on Multidisciplinary technical Sciences is composed of three scientific branches: information technology, electrical engineering and biology. The number of doctoral students is about 50 and 10 PhD degrees were granted during the last 2 years. Some representative results: - Algorithmic combination of logic, analog, and noise array signals on a chip, resulting true random bit patterns, as well - Cellular Many-core chips used for solving Navier-Stokes and geothermic PDEs - Detection of auditory events by using cellular processor array algorithms - Many-target detection and tracking via cellular wave algorithms - Design of nano-antenna array elements - Molecular dynamics simulation on Supercomputers - Determining visual saliency - models and human tests - Design and characterization of MEMS bionic brain interfaces/probes - Designs and testing deep submicron CMOS circuits for hyper acuity in time - 3D tactile sensor array - design, testing and software environment - Visual mouth animation for deaf people via a mobile phone - Moving the limbs of spinal cord injured patients via electronic non-invasive stimuli - Development of new tools of human language technology including some special classes of problems given by their specific ontology The emerging common multidisciplinary mindset of the doctoral student body. In addition to about 100 publications during the grant period, an annual research reporting symposium has been organized and its content published