Because of locality of communication in space, a computing medium such as a Cellular Automata (CA) can scale abitrarily in size, thus providing a machine which power can grow arbitrarily. This same locality , however, makes the programming difficult, and -CA as a computing device- ... look more like a toy for mathematicians fond of funny images. They are mostly known for the game of life rule, which allthough universal, is light-years away from real practical computations. We will show that a CA rule can be real General Purpose, and even an efficient computing device. We use two main ingredient: 1- we have develop a compiler and a simulation platform allowing to program complex CA with radius of 20 and thousands of gates, using layers, and object oriented software, and an efficient execution exploiting the SIMD integer operations. 2- we obtain general purpose-ability by implementing SELF DEVELOPING SYSTEM.

The GPCA rule is not finalised yet, allthough we will be able to present several simulations, showing the feasibility. First, we show a CA rule able to do homogeneization of agents distributed on the CA medium. When the agents are hierachically organized, the homogeneisation still work on the hierarchy. Second we present the current status of our GPCA. It executes instructions send by a host, which propage through the medium like a wave. The first kind of instructions are local instructions: the effect is immediate as the instructions traverse a CA cell. Local instructions allow to select agents, and set registers. The second kind of instructions call collective instructions, define regions on the CA, in which a sustained activy takes blace by a succession of 4- 5 region-waves giving birth to each other, at specific places. They are the equivalent of the 4 - 5 cycles, needed to execute a machine instruction in a processor. Those instruction are micro-programmed, the micro-instructions are associated to each region wave. For the moment being we have implemented only 3 collective instructions, the easiest one: Election, Computation, and Duplication. We will show a development obtained by sending 8 Duplications to an initially single agent. It generates 256 offsprings, in only 600 iterations of the CA rules, which illustrates the scalability. The finalised GPCA will make use of 4 more elaborate instructions, whose functionning is described in detail in a report, but not yet implemented. The GPCA cell will have around 64 bits of memory, and 20,000 gates. For the moment, it has only 6000 gates.

We are used to think of computer as General-Purpose machine with arbitrary large memory. The GPCA is a General-Purpose machine with arbitrary large power.