Title :
Graph Theoretical Representation of Grid-based ANN Architectures for VLSI Implementations
Author :
Stilkerich, Stephan C.
Author_Institution :
EADS Corp. Res. Center, Munich
Abstract :
The System-on-Chip design of purely digital architectures, which are based on massively parallel Markov random field (MRF) processing principles is so far an unstructured, time consuming, fault-prone and complex task. Up to now a toolkit is not available to systematically support the VLSI design task in a single coherent environment and along a seamless design flow for various digital semiconductor-technologies. In this contribution we report on a completely technology-independent and graph-theoretical approach for the VLSI design of massively parallel MRF processing devices. The paper is finalized by selected results, which show generated graphs, synthesis results and prototypical implementations in FPGA technologies. All together these results demonstrate the ability of the proposed graph-theoretical approach and manifest the industrial relevance of the developed tool-kit.
Keywords :
Markov processes; VLSI; artificial intelligence; field programmable gate arrays; graph theory; neural nets; system-on-chip; FPGA technology; MRF processing principle; Markov random field; VLSI implementation; artificial neural network; digital semiconductor-technology; field programmable gate array; graph theoretical representation; grid-based ANN architecture; system on chip; Entropy; Field programmable gate arrays; Image analysis; Markov random fields; Parallel processing; Radiation hardening; Signal processing; Signal processing algorithms; Space technology; Very large scale integration;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688706