Bio-inspired cellular machines:towards a new electronic paper architecture

Information technology has only been around for about fifty years. Although the beginnings of automatic calculation date from as early as the 17th century (W. Schickard built the first mechanical calculator in 1623), it took the invention of the transistor by W. Shockley, J. Bardeen and W. Brattain in 1947 to catapult calculators out of the laboratory and produce the omnipresence of information and communication systems in today's world. Computers not only boast very high performance, capable of carrying out billions of operations per second, they are taking over our world, working their way into every last corner of our environment. Microprocessors are in everything, from the quartz watch to the PC via the mobile phone, the television and the credit card. Their continuing spread is very probable, and they will even be able to get into our clothes and newspapers. The incessant search for increasingly powerful, robust and intelligent systems is not only based on the improvement of technologies for the manufacture of electronic chips, but also on finding new computer architectures. One important source of inspiration for the research of new architectures is the biological world. Nature is fascinating for an engineer: what could be more robust, intelligent and able to adapt and evolve than a living organism? Out of a simple cell, equipped with its own blueprint in the form of DNA, develops a complete multi-cellular organism. The characteristics of the natural world have often been studied and imitated in the design of adaptive, robust and fault-tolerant artificial systems. The POE model resumes the three major sources of bio-inspiration: the evolution of species (P: phylogeny), the development of a multi-cellular organism by division and differentiation (O: ontogeny) and learning by interaction with the environment (E: epigenesis). This thesis aims to contribute to the ontogenetic branch of the POE model, through the study of three completely original cellular machines for which the basic element respects the six following characteristics: it is (1) reconfigurable, (2) of minimal complexity, (3) present in large numbers, (4) interconnected locally with its neighboring elements, (5) equipped with a display capacity and (6) with sensor allowing minimal interaction. Our first realization, the BioWall, is made up of a surface of 4,000 basic elements or molecules, capable of creating all cellular systems with a maximum of 160 × 25 elements. The second realization, the BioCube, transposes the two-dimensional architecture of the BioWall into a two-dimensional space, limited to 4 × 4 × 4 = 64 basic elements or spheres. It prefigures a three-dimensional computer built using nanotechnologies. The third machine, named BioTissue, uses the same hypothesis as the BioWall while pushing its performance to the limits of current technical possibilities and offering the benefits of an autonomous system. The convergence of these three realizations, studied in the context of emerging technologies, has allowed us to propose and define the computer architecture of the future: the electronic paper

Dynamic parallel reconfiguration for self-adaptive hardware architectures

Adaptive Hardware Systems can rely on software or hardware adaptation. Software adaptation can be globally assimilated to mode switching, either at a technological or hardware level (DVFS, Idle processor mode ...), or at the application level (bandwidth adaptation in telecommunication, multispectral cameras, ...). Hardware adaptation corresponds to a deeper change in the internal organization of the computing architecture of an embedded system. It enables more powerful adaptation but is currently limited by the reconfiguration (tool and architecture) of today's FPGA devices. We present in this paper a multi-FPGA platform designed to exhibit unique computing capabilities. The joint design of the electronic board and the internal architecture of each reconfigurable device permits dynamic parallel (and not partial) reconfiguration of several parts of the system while maintaining global routing and local computation in the rest of the system. Dynamic parallel reconfiguration and technological independence are enabled by considering reconfiguration at coarse grain. We describe in the paper the hardware elements composing the platform. The specific design of the global system allowed us to reach a fully operational platform. We present statistical experiments to evaluate the inter-chip network capacity which show that our platform supports up to 18 parallel reconfigurations per second

CONFETTI : A reconfigurable hardware platform for prototyping cellular architectures

In this article, we describe a novel hardware platform aimed at the realization of cellular architectures. The system is built hierarchically from a very simple computing unit, called ECell. Several of these units can then be connected, using a high-speed serial communication protocol, to a more complex structure called the UltraStack. Consisting of four different kinds of interconnected boards (computational, routing, power supply, and display), these stacks can then be joined together to form an arbitrarily large parallel network of programmable circuits. This structure, while theoretically universal in its operation, is however particularly suited for the implementation of cellular computing applications

Bio-inspired Systems with Self-developing Mechanisms

Bio-inspired systems borrow three structural principles characteristic of living organisms: multicellular architecture, cellular division, and cellular differentiation. Implemented in silicon according to these principles, our cellular systems are endowed with self-developing mechanisms like configuration, cloning, cicatrization, and regeneration. These mechanisms are made of simple processes such as growth, load, branching, repair, reset, and kill. The hardware simulation and hardware implementation of the self-developing mechanisms and their underlying processes constitute the core of this paper

Bio-inspired self-organizing cellular systems

Bio-inspiration borrows three properties characteristic of living organisms: multicellular architecture, cellular division, and cellular differentiation. Implemented in silicon according to these properties, our self-organizing systems are able to grow, to self-replicate, and to self-repair. The growth and branching processes, performed by the so-called Tom Thumb algorithm, lead thus to the configuration and cloning mechanisms of the systems. The repair processes allow its cicatrization and regeneration mechanisms. The cellular design and hardware implementation of these mechanisms constitute the core of this paper. (C) 2008 Elsevier Ireland Ltd. All rights reserved

Pruning self-organizing maps for cellular hardware architectures

Self-organization is a bio-inspired feature that has been poorly developed when it comes to talking about hardware architectures. Cellular computing approaches have tackled it without considering input data. This paper introduces the SOMA architecture, which proposes an approach for self-organizing machine architectures. In order to achieve the desirable features for such machine, we propose PCSOM, a bio-inspired approach for self-organizing cellular hardware architectures in function of input data. PCSOM is a vector quantization algorithm defined as a network of neurons interconnected through synapses. Synapse pruning makes it possible to organize the cellular system architecture (i.e., topology and configuration of computing elements) in function of the content of input data. We present performance results of the algorithm and we discuss the benefits of PCSOM compared to other existing algorithms

Pruning Self-Organizing Maps for Cellular Hardware Architectures

International audienceSelf-organization is a bio-inspired feature that has been poorly developed when it comes to talking about hardware architectures. Cellular computing approaches have tackled it without considering input data. This paper introduces the SOMA architecture, which proposes an approach for self-organizing machine architectures. In order to achieve the desirable features for such machine, we propose PCSOM, a bio-inspired approach for self-organizing cellular hardware architectures in function of input data. PCSOM is a vector quantization algorithm defined as a network of neurons interconnected through synapses. Synapse pruning makes it possible to organize the cellular system architecture (i.e. topology and configuration of computing elements) in function of the content of input data. We present performance results of the algorithm and we discuss the benefits of PCSOM compared to other existing algorithms

SCALP ::self-configurable 3-D cellular adaptive platform

Parallel computation has appeared as the most promising technique to circumvent the limitations imposed by power consumption in order to continue increasing computation power, making thus manycore architectures a promising computer organization approach. Interconnecting and coordinating such high amount of computation nodes in an efficient manner is a hot research topic, several approaches to Network-on-chip architectures propose solutions for this. This paper presents a 3D multi-FPGA hardware platform permitting to prototype 3D NoC architectures with dynamic topologies. More precisely, we intend to use it to prototype self-adaptive and self-organizing hardware architectures in which the computation performed by a node and the interconnections between these nodes can be dynamically modified, being these modifications triggered by the platform itself. This paper presents the overall hardware organization and gives some hints about how to use it