GPU (graphics processing unit) processing method for high-dimensional data stream in irregular stream

Abstract

The invention discloses a GPU (graphics processing unit) processing method for a high-dimensional data stream in an irregular stream, and belongs to a processing method for the high-dimensional data stream. The method comprises the steps that a GPU-based data stream parallel computation model performs parallel computation processing on the high-dimensional data stream in the irregular stream of a data source and then sends the high-dimensional data stream to a client end; a CPU (central processing unit) host unit is a core for logic judgment and control and is used for serial computation; all or part of synopsis data structures are transferred into a video memory of GPU equipment; when the client end provides an inquiry request, the CPU host unit is in charge of calling a kernel program of the GPU equipment and executing an inquiry algorithm kernel on the synopsis data structures in the video memory of the GPU equipment, an inquiry result is returned to the CPU host unit, and finally the CPU host unit converts the result into a readable final inquiry result and returns the readable final inquiry result to the client end. According to the GPU processing method, the relevance between the high-dimensional data streams under a synchronous sliding window mode can be precisely identified on line; the outstanding speed advantage is realized, and the requirement on instantaneity of the high-dimensional data stream is well met.

Description

technical field [0001] The invention relates to a processing method of high-dimensional data flow, in particular to a GPU processing method of high-dimensional data flow in irregular flow. Background technique [0002] GPU (Graphic Processing Unit), the Chinese translation is "graphics processing unit". The GPU is the "heart" of the graphics card, which is equivalent to the role of the CPU in the computer. The GPU has a fairly high memory bandwidth and a large number of execution units, which can help the CPU to perform some complex calculations, reducing the graphics card's dependence on the CPU. [0003] Traditionally, the application of GPU is limited to processing graphics rendering computing tasks, which is undoubtedly a great waste of computing resources. With the continuous improvement of GPU programmability, the research on using GPU to complete general computing is gradually becoming active. Computing that uses GPUs for areas other than graphics rendering is call...

AI Technical Summary

Problems solved by technology

(1) The access sequence of elements in an irregular flow may be intermittent, skipped or repeated

(2) The access sequence of elements in the irregular flow may be dynamically generated, and may also be selected according to conditions

(3) Due to the uncertainty of the access sequence of elements in the irregular flow, there is no special relationship between its actual length and the access length, and both may be uncertain

When the data scale is large, the data is often used as the medium of disk or tape, so the execution of query operations requires a large number of I / O exchanges, which is inefficient and cannot meet the needs of real-time systems

[0013] Due to the ever-changing and unpredictable characteristics of the data stream itself, as well as the generation of data stream bursts (Burst), higher requirements are placed on the data stream load capacity. To meet the real-time requirements, the study and use of high-speed stream processors to improve the throughput of data stream processing has become one of the hot issues in the field of data stream processing research.

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