Efficient Implementation of the THSOM Neural Network
Recent trends in microprocessor design clearly show that the multicore processors are the answer to the question how to scale up the processing power of today’s computers. In this article we present our C implementation of the Temporal Hebbian Self-organizing Map (THSOM) neural network. This kind of neural networks have growing computational complexity for larger networks, therefore we present different approaches to the parallel processing – instruction based parallelism and data-based parallelism or their combination. Our C implementation of THSOM is modular and multi-platform, allowing us to move critical parts of the algorithm to other cores, platforms or use different levels of the instruction parallelism yet still run exactly the same computational flows – maintaining good comparability between different setups. For our experiments, we have chosen a multicore x86 system.
KeywordsNetwork Size Lookup Table Cache Size Temporal Weight Best Match Unit
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