Prototype Design of Global Common Module for ATLAS Experiment’s Phase-II Upgrade
IEEE Transactions on Nuclear Science(2023)
Brookhaven Natl Lab
Abstract
A new Global Trigger subsystem will be installed in the Level-0 Trigger as part of the High-Luminosity Large Hadron Collider (HL-LHC) upgrade of ATLAS during the upcoming Long-Shutdown 3. It will feature new and improved trigger hardware and algorithms, and an increased maximum output rate of 1 MHz. The Global Trigger will run offline-like trigger algorithms on full-granularity data, gathered from several subdetectors and trigger processing subsystems. A single global common module (GCM) hardware is implemented across the Global Trigger system to be used as a multiplexer processor (MUX), global event processor (GEP), and global-to-central trigger processor interface (gCTPi). This common hardware platform method will minimize the complexity of the firmware and simplify the system design and long-term maintenance. The GCM prototype is a Advanced Telecommunications Computing Architecture (ATCA) front form factor board with two Xilinx Virtex UltraScale+ field-programmable gate array (FPGA) VU13P and one ZYNQ UltraScale+ FPGA ZU19EG and 17 25.78125-Gb/s FireFly duplex optical modules on it. The total power consumption of this board must be less than 350 W, and the temperature of the optical modules should be less than 70 °C in the worst case. The VU13Ps serve as algorithms processor nodes such as MUX, GEP, and gCTPi, and the ZU19EG with Peta Linux OS running on it is used as command/control/readout unit to configure and monitor the board and communicate with the ATLAS detector control system (DCS). The development of an ATCA blade with three large FPGAs and about 200 optical links running at 25 Gb/s is a very challenging task, and the successful test results have demonstrated this GCM prototype as an advancement of state-of-the-art electronics module design in high energy physics (HEP) experiments. This article presents the hardware design considerations, functionalities, and performance test results of this GCM prototype.
MoreTranslated text
Key words
ATLAS,global common module (GCM),Global Trigger,LHC
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined