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.

The multicellular structure of biological organisms and the interpretation in each of their cells of a chemical program (the DNA string or genome ) is the source of inspiration for the Embryonics (embryonic electronics) project, whose final objective is the design of highly robust integrated circuits, endowed with properties usually associated with the living world: self-repair and self-replication. In this article, we provide an overview of our latest research in the domain of the self-replication of processing elements within a programmable logic substrate, a key prerequisite for achieving system-level fault tolerance in our bio-inspired approach.

In 1953, Crick and Watson published their landmark paper revealing the detailed structure of the DNA double helix. Several years earlier, von Neumann embedded a very complex configuration, a universal interpreter-copier, into a cellular array. Astoundingly, the structure of this configuration, able to realize the self-replication of any computing machine, including a universal Turing machine, shares several common traits with the structure of living cells as defined by Crick and Watson's discovery. To commemorate the 100th anniversary of von Neumann's birth, this paper presents a macroscopic analysis of self-replication in computing machines using three examples. After describing self-replication in von Neumann's universal interpreter-copier, we will revisit the famous self-replicating loop designed by Langton in 1984. In order to overcome some of the major drawbacks of Langton's loop, namely, its lack of functionality and the fact that it is ill-adapted for a realization in electronic circuits, we present a novel self-replicating loop, the Tom Thumb loop. Endowed with the same capabilities as von Neumann's interpreter-copier, i.e., the possibility of replicating computing machines of any complexity, our loop is moreover specifically designed for the implementation of self-replicating structures in programmable digital logic.

The growth and operation of all living beings are directed by the interpretation, in each of their cells, of a chemical program, the DNA string or genome. This process is the source of inspiration for the Embryonics (embryonic electronics) project, whose final objective is the design of highly robust integrated circuits, endowed with properties usually associated with the living world: self-repair (cicatrization) and self-replication. The Embryonics architecture is based on four hierarchical levels of organization. (1) The basic primitive of our system is the molecule, a multiplexer-based element of a novel programmable circuit. (2) A finite set of molecules makes up a cell, essentially a small processor with an associated memory. (3) A finite set of cells makes up an organism, an application-specific multiprocessor system. (4) The organism can itself replicate, giving rise to a population of identical organisms. We begin by describing in detail the implementation of an artificial cell characterized by a fixed architecture, showing that multicellular arrays can realize a variety of different organisms, all capable of self-replication and self-repair. In order to allow for a wide range of applications, we then introduce a flexible architecture, realized using a new type of fine-grained field-programmable gate array whose basic element, our molecule, is essentially a programmable multiplexer. We describe the implementation of such a molecule, with built-in self-test, and illustrate its use in realizing two applications: a modulo-4 reversible counter (a unicellular organism) and a timer ( a complex multicellular organism). We describe our ongoing research efforts to meet three challenges: a scientific challenge, that of implementing the original specifications formulated by John von Neumann for the conception of a self-replicating automaton; a technical challenge, that of realizing very robust integrated circuits capable of self-repair and self-replication; and a biological challenge, that of attempting to show that the microscopic architectures of artificial and natural organisms, i.e., their genomes, share common properties.

In this short article, we argue that von Neumann's quintessential message with respect to self-replicating automata is genotype + ribotype = phenotype. Self-replication occurs in analogy to nature: The description (genotype) written on the input tape is translated via a ribosome (ribotype) so as to create the offspring universal constructor (phenotype).

Biological organisms are among the most intricate structures known to man, exhibiting highly complex behavior through the massively parallel cooperation of numerous relatively simple elements, the cells. As the development of computing systems approaches levels of complexity such that their synthesis begins to push the limits of human intelligence, engineers are starting to seek inspiration in nature for the design of computing systems, both at the software and at hardware levels. We present one such endeavor, notably an attempt to draw inspiration from biology in the design of a novel digital circuit: a field-programmable gate array (FPGA). This reconfigurable logic circuit will be endowed with two features motivated and guided by the behavior of biological systems: self-replication and self-repair.

The growth and the operation of all living beings are directed through the interpretation, in each of their cells, of a chemical program, the DNA string or genome. This process is the source of inspiration for the Embryonics (embryonic electronics) project, whose final objective is the conception of very large scale integrated circuits endowed with properties usually associated with the living world: self-repair (cicatrization) and self-replication. We begin by showing that any logic system can be represented by an ordered binary decision diagram (OBDD), and then embedded into a fine-grained field-programmable gate array (FPGA) whose basic cell is a multiplexer with programmable connections. The cellular array thus obtained is perfectly homogeneous: the function of each cell is defined by a configuration (or gene) and all the genes in the array, each associated with a pair of coordinates, make up the blueprint (or genome) of the artificial organism. In the second part of the project, we add to the basic cell a memory and an interpreter to, respectively, store and decode the complete genome. The interpreter extracts from the genome the gene of a particular cell as a function of its position in the array (its coordinates) and thus determines the exact configuration of the relative multiplexer. The considerable redundancy introduced by the presence of a genome in each cell has significant advantages: self-replication (the automatic production of one or more copies of the original organism) and self-repair (the automatic repair of one or more faulty cells) become relatively simple operations. The multiplexer-based FPGA cell and the interpreter are finally embedded into an electronic module; an array of such modules make it possible to demonstrate self-repair and self-replication.

If one considers life on Earth since its very beginning, three levels of organization can be distinguished: the phylogenetic level concerns the temporal evolution of the genetic programs within individuals and species, the ontogenetic level concerns the developmental process of a single multicellular organism, and the epigenetic level concerns the learning processes during an individual organism's lifetime. In analogy to nature, the space of bio-inspired hardware systems can be partitioned along these three axes-phylogeny, ontogeny and epigenesis (POE)-giving rise to the POE model. This paper is an exposition and examination of bio-inspired systems within the POE framework, with our goals being: (1) to present an overview of current-day research, (2) to demonstrate that the POE model can be used to classify bio-inspired systems, and (3) to identify possible directions for future research, derived from a POE outlook. We discuss each of the three axes separately, considering the systems created to date and plotting directions for continued progress along the axis in question.

The concept of binary decision trees is extended to include multiple output Boolean functions. A systematic and programmable method is then developed for the minimization of trees realizing multiple output incompletely specified functions. Further simplification of minimal trees can be achieved through state reduction methods to obtain subminimal decision algorithms. Possible physical realizations of decision trees and algorithms as well as their applications are discussed.