Systemic computation using graphics processors

Authors:
Marjan Rouhipour;Peter J. Bentley;Hooman Shayani
Affiliations:
BIHE University, The Bahá'í Institute for Higher Education, Iran;Department of Computer Science, University College London, London;Department of Computer Science, University College London, London
Venue:
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
Year:
2010

Citing 12
Cited 2

P systems with active membranes: attacking NP-complete problems

Journal of Automata, Languages and Combinatorics
Brook for GPUs: stream computing on graphics hardware

ACM SIGGRAPH 2004 Papers
A systemic computation platform for the modelling and analysis of processes with natural characteristics

Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
The Perplexus bio-inspired reconfigurable circuit

AHS '07 Proceedings of the Second NASA/ESA Conference on Adaptive Hardware and Systems
GPU acceleration of cutoff pair potentials for molecular modeling applications

Proceedings of the 5th conference on Computing frontiers
Rapid evaluation and evolution of neural models using graphics card hardware

Proceedings of the 10th annual conference on Genetic and evolutionary computation
Systemic computation: A model of interacting systems with natural characteristics

International Journal of Parallel, Emergent and Distributed Systems - Emergent Computation
Eating Data Is Good for Your Immune System: An Artificial Metabolism for Data Clustering Using Systemic Computation

ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Designing Biological Computers: Systemic Computation and Sensor Networks

Bio-Inspired Computing and Communication
Pure bigraphs: Structure and dynamics

Information and Computation
Crash-proof systemic computing: a demonstration of native fault-tolerance and self-maintenance

ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
Fault Tolerance Using Dynamic Reconfiguration on the POEtic Tissue

IEEE Transactions on Evolutionary Computation

Natural born computing

MEMICS'11 Proceedings of the 7th international conference on Mathematical and Engineering Methods in Computer Science
Introducing the FPGA-Based hardware architecture of systemic computation (HAoS)

MEMICS'11 Proceedings of the 7th international conference on Mathematical and Engineering Methods in Computer Science

Quantified Score

Hi-index	0.00

Visualization

Abstract

Previous work created the systemic computer - a model of computation designed to exploit many natural properties observed in biological systems, including parallelism. The approach has been proven through two existing implementations and many biological models and visualizations. However to date the systemic computer implementations have all been sequential simulations that do not exploit the true potential of the model. In this paper the first parallel implementation of systemic computation is introduced. The GPU Systemic Computation Architecture is the first implementation that enables parallel systemic computation by exploiting multiple cores available in graphics processors. Comparisons with the serial implementation when running a genetic algorithm at different scales show that as the number of systems increases, the parallel architecture is several hundred times faster than the existing implementations, making it feasible to investigate systemic models of more complex biological systems.