Replication time is among the most important components of a bacterial cell's reproductive fitness. Paradoxically, larger cells replicate in less time than smaller cells despite the fact that assembling a larger cell requires collecting and combining increased quantities of raw materials. This feat is accomplished through the prodigious use of parallel processing, chiefly, the translation of mRNA into protein by tens of thousands of ribosomes acting in parallel. The massive over expression of ribosomes permits protein synthesis, the limiting step in replication, to occur at a rate and scale that would be otherwise impossible. In computer science, spatial parallelism is the distribution of work across the nodes of a distributed-memory multicomputer system. Despite the fact that a non-negligible fraction of artificial life research is grounded in formulations based on spatially parallel substrates, there have been no examples of artificial organisms that use spatial parallelism to replicate in less time than smaller organisms. This paper describes artificial cells defined using a combinator-based artificial chemistry that replicate in less time than smaller cells. This is achieved by employing extra copies of programs implementing the limiting steps in the process used by the cells to synthesize their component parts. Significant speedup is demonstrated, despite the increased complexity of control and export processes necessitated by the use of a parallel replication strategy.

An object-oriented combinator chemistry was used to construct an artificial organism with a system architecture possessing characteristics necessary for organisms to evolve into more complex forms. This architecture supports modularity by providing a mechanism for the construction of executable modules called methods that can be duplicated and specialized to increase complexity. At the same time, its support for concurrency provides the flexibility in execution order necessary for redundancy, degeneracy and parallelism to mitigate increased replication costs. The organism is a moving, self-replicating, spatially distributed assembly of elemental combinators called a roving pile . The pile hosts an asynchronous message passing computation implemented by parallel sub-processes encoded by genes distributed through out the pile like the plasmids of a bacterial cell.

An artificial chemistry with composition devices borrowed from object-oriented and functional programming languages was introduced in prior work. Actors in object-oriented combinator chemistry are embedded in space and subject to diffusion; since they are neither created nor destroyed, mass is conserved. This paper further develops these ideas and applies them in significant ways. First, it introduces the concept of a self-replicating systems normalized complexity. Normalized complexity permits comparisons between artificial organisms defined in different virtual worlds by explicitly accounting for the relative complexities of both organism and world. Second, object-oriented combinator chemistry is used to define a parallel, asynchronous, spatially distributed self-replicating system modeled in part on the living cell. This system is strongly constructive since interactions among its parts results in the construction of more of these same parts; constructed parts are assembled from elements of a few primitive types. The systems high normalized complexity is contrasted with that of a simple composome, which is also defined.