Enhanced parallel SOM based on heterogeneous system platform

In this paper, we propose an enhanced parallel Self organizing Map (SOM) framework based on heterogeneous system platform, specifically Central Processing Unit (CPU) and Graphic Processing Unit (GPU) soldered together on a single chip.The framework is to improve speed of parallel SOM using GPU since processing parallel SOM on GPU burden by communication latency due to isolate device architecture with CPU.The parallel SOM has been extended to heterogeneous system platform and double kernel for calculation distance and find Best Matching Unit (BMU) are introduced.The results are tested using benchmark data on two different platforms: GPU and heterogeneous system. The proposed framework shows improvement compared to standard parallel SOM on GPU and heterogeneous system