A systemic computation platform for the modelling and analysis of processes with natural characteristics

Abstract

Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1] introduced systemic computation, a model of interacting systems with natural characteristics. Following this work, here we introduce the first platform implementing such computation, including programming language, compiler and virtual machine. To investigate their use we then provide an implementation of a genetic algorithm applied to the travelling salesman problem and also explore how SC enables self-adaptation with the minimum of additional code.

Systemic Computation Using Graphics Processors

“…Systemic computation is a new bio-inspired model of computation that has shown considerable success for biological modeling and bio-inspired computation [6][7][8][9][10][11][12][13][14]. However until now it has only been available as a serial simulation running on conventional processors.…”

“…The simulation was implemented in ANSI C on a PowerBook Macintosh G4, enabling systemic computation programs to be simulated using conventional computer processors. Later work by Le Martelot created a second implementation on PCs with a higher-level language and visualization tools [2,[6][7][8][9][10][11][12]14]. Other work provided a discussion on the use of sensor networks to implement a systemic computer [13].…”

“…Although not the first such model, SC is the result of considerable research into bio-inspired computation and biological modelling, and has been developed into a working computer architecture [1,6]. To date, two simulations of this architecture have been developed, with corresponding machine and programming languages, compilers and graphical visualiser [1,6].…”

“…To date, two simulations of this architecture have been developed, with corresponding machine and programming languages, compilers and graphical visualiser [1,6]. Extensive work has shown how this form of computer enables useful biological modeling and bio-inspired algorithms to be implemented with ease [7][8][9][10][11] and how it enables properties such as fault-tolerance and self-repairing code [12].…”

Methods for improving simulations of biological systems: systemic computation and fractal proteins

“…Previous work simulated parallelism using a virtual machine (Le Martelot et al 2007b). Work to create a grid-based SC parallel computer capable of running over any network of computers is underway enable abstraction at any level of detail SC forces the modeller explicitly to think about abstraction as they choose what each individual system should model; there are no limits (except those imposed by finite memory of computers) on the level of abstraction or detail that can be supported enable automated analysis (e.g.…”