GStreamMiner: A GPU-accelerated Data Stream Mining Framework

Due to the continuous, unbounded, and dynamic characteristics of the streaming data, mining data streams becomes a very challenging task. When analyzing online data streams, it is necessary to produce accurate results in a very short amount of time. The parallel processing power of Graphics Processing Units (GPUs) can be used to accelerate the processing and produce results in a timely manner. In this paper, we present GStreamMiner, a GPU-accelerated data stream mining framework and demonstrate its application using outlier detection over continuous streaming data as a case study. The demo software provides a visual interface which is continuously get updated with new results as the data stream progresses. It also facilitates the users to compare the performance of the GPU and CPU versions of the outlier detection algorithm.