Lei Zhang;Junfeng Yang;Zhengyang Sun;Jinrui Zeng;Ke Sun;Yi Li
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引用次数: 0
Abstract
The data acquisition system plays an increasingly important role in high-energy physics experiments. The expansion of the experimental scale requires the data acquisition system to have enhanced online data processing capabilities. The D-Matrix system is designed as a general distributed stream processing platform, aiming to make more use of heterogeneous computing units, such as FPGA, for suitable online data processing to optimize both processing speed and latency. In the D-Matrix system, to facilitate the design of various data processing modules in high-energy physics experiments, we abstract the concepts of basic patterns and derived modules. Based on these concepts, the D-Matrix system is designed with a series of generic data stream processing modules to accomplish various complex data processing by cascading these generic modules. This article introduces the existing base patterns and derives stream processing modules in the D-Matrix system based on FPGA-based hardware and also describes the implementation of these modules in the CSR External-target Experiment (CEE).
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.