Research On Data Stream Processing Methods Based On GPU

As a kind of novel stream microprocessor, GPU has the characters of stream processing model. Because its inexpensive, widespread, powerful computing horsepower and high bandwidth general purpose parallel computing device, the HPC capability of GPU draws more and more domestic and abroad scholars'attention. As a new type of data, data stream has the properties of fast, continuous arrival, potential immensity capacity. How to increase data stream processing system throughput and real time processing ability of data stream becomes one of key problems in data stream research area.The paper focuses on the application study of General-purpose computing on Graphic Processing Unit on the data streams, especially, in the irrergular streams the HPC processing of high dimensional data streams is the major feature of the paper; presents a GPU data stream parallel computing frame model. Doing the esearch on both regular streams and multiple-dimension stream processing method separately is to analyse the part of time-consuming and try to transfer the serial CPU algorithm to the GPU.According to the regular data streams, based on maths model of 3D image reconstruction and matrix theory, ET 3D image reconstruction algorithm based on GPU is processed, which is simulated on the CUD A platform of GPU to the regular project stream data. The experimental result is that the processing speed is increased by 50 times under the circumstance of resource-constraints, at the same time, the quality of the image is guaranteed.According to the high dimensional data streams, GPU-based processing model and specific and practical architecture for high dimensional data streams in the irregular streams are proposed, meanwhile, based on Compute Unified Device Architecture (CUDA), canonical correlation analysis between two multiple dimensions data streams using data cube pattern and dimensionality-reduction technique is carried out in this framework. The theoretical analysis and experimental results show that the parallel processing method can online detect correlations between multiple dimension data streams accurately in the synchronous sliding window mode. According to the pure CPU method, this method has significant speed advantage, well meet the real-time requirement of high-dimensional data streaming and can be applied to the field of high-dimensional data stream mining widely.