首页> 外文期刊>Journal of instrumentation: an IOP and SISSA journal >A Pattern Recognition Mezzanine based on Associative Memory and FPGA technology for Level 1 Track Triggers for the HL-LHC upgrade
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A Pattern Recognition Mezzanine based on Associative Memory and FPGA technology for Level 1 Track Triggers for the HL-LHC upgrade

机译:基于关联存储器和FPGA技术的模式识别夹层,用于HL-LHC升级的1级跟踪触发器

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The increment of luminosity at HL-LHC will require the introduction of tracker information at Level-1 trigger system for the experiments in order to maintain an acceptable trigger rate for selecting interesting events despite the one order of increased magnitude in the minimum bias interactions. In order to extract the track information in the required latency (~5–10 μs depending on the experiment), a dedicated hardware processor needs to be used. We here propose a prototype system (Pattern Recognition Mezzanine) as core of pattern recognition and track fitting for HL-LHC experiments, combining the power of both Associative Memory custom ASIC and modern Field Programmable Gate Array (FPGA) devices.
机译:HL-LHC的光度增加将需要在Level-1触发系统上引入用于实验的跟踪器信息,以保持可接受的触发速率以选择有趣的事件,尽管最小偏差交互作用的幅度增加了一个数量级。为了以所需的延迟时间(约5–10μs,取决于实验)提取轨道信息,需要使用专用的硬件处理器。我们在这里提出一个原型系统(模式识别夹层)作为HL-LHC实验的模式识别和轨道拟合的核心,结合联合存储器定制ASIC和现代现场可编程门阵列(FPGA)器件的功能。

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