Andrew A. Duncan

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This paper reports on the design issues and subsequent performance of a soft intellectual property (IP) core implementation of a self-organizing neural network. The design is a development of a previous 0.65-/spl mu/m single silicon chip providing an array of 256 neurons, where each neuron stores a 16 element reference vector. Migrating the design to a soft(More)
COBRA is a behavioral high level synthesis tool for datapath dominated applications. It uses a regular architecture which has been previously shown to significantly reduce the area of synthesised datapaths and integrates the traditional scheduling, allocation and binding tasks into one global optimisation. Optimisation is performed using simulated annealing(More)
This paper presents an overview of the COBRA-ABS behavioural high-level synthesis tool. COBRA-ABS has been designed to synthesise custom architectures for arithmetic intensive algorithms, specified in C, for implementation on multi-FPGA Custom Computing Machine (FCCM) platforms. It performs globally optimising high level synthesis using simulated annealing,(More)
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