Dynamic Structural and Computational Resource Allocation for Self-Organizing Architectures
Résumé
Efficient dynamic allocation of computation resources can enable significant improvements in terms of performance and /or power consumption of hardware architectures.In this paper, we propose three bio-inspired mechanisms for self-organizing cellular hardware architecture built on top of the Cellular Self-Organizing Map (CSOM) vector quantization algorithm.Taking inspiration from the self-organization present in living organisms, we make use of structural and functional plasticity through the modulation of synapses and neurons usage.SPCSOM extends CSOM through synapse pruning and sprouting, yielding a SOM that can dynamically modulate its topology throughout its lifetime. MSPCSOM adds a neuron migration method between different clusters of the map.SBMCSOM deals with multiple SOMs handling different tasks by dynamically reassigning neurons between the tasks, seeking a trade-off between the quantization error of each SOM.Algorithms are intended to run in SCALP, a multi-FPGA hardware platform for prototyping self-organizing networks.