Growing large-scale cellular arrays of processors

Molecular-scale integrated circuits will provide hardware designers with astounding computational resources. However, current design methodologies—which already struggle to exploit the resources available today—are ill-suited to the complexity and high fault rates of these novel technologies. Nature, on the other hand, has evolved ways of coping with these issues. A human being consists of approximately 60 trillion (60× 1012) cells, ceaselessly operating throughout the lifetime of the organism. Faults occur at a very high rate, but (in the majority of cases) are successfully detected and repaired with little or no effect on the organism. It is therefore legitimate to wonder if it is possible to draw inspiration from nature to find ways to cope with the complexity of molecular-scale electronics. One of the basic mechanisms behind the resilience of biological organisms is cellular division, i.e., the ability of the cells to self-replicate. Indeed the idea of self-replicating computing machines has a long history, starting in the 1950s with the seminal work of John von Neumann1 and continuing in the 1980s with the research of Chris Langton.2 More recently, the predicted features of nanoelectronic devices have sparked a renewed interest in the topic.3–6 Our own research7–10 addresses the development of self-replication approaches that can be integrated within complex digital systems able to operate in the presence of faulty components. More recently, we have focused on the transposition of biological mechanisms to theworld of computer hardware. 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) and this process is the source of inspiration for our Embryonics (embryonic electronics) project. Our 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. Figure 1. The four hierarchical levels of organization of an Embryonics system.