24th IEEE Real Time Conference - ICISE, Quy Nhon, Vietnam

Session

Oral presentations, CANPS Award

Day 5 - Morning

26 Apr 2024, 09:00

90. Evaluation of SmartNIC Devices for use in Trigger and Data Acquition Systems

Adam Abed Abud (CERN), Andreas Klavenes Berg (Norwegian University of Science and Technology (NTNU) (NO)), Enrico Gamberini (CERN), Roland Sipos (CERN)

26/04/2024, 09:00

Data Acquisition and Trigger Architectures

Oral presentation

This contribution presents an evaluation of SmartNIC devices in the context of Trigger and Data AcQquisition (TDAQ) systems. SmartNIC devices represent an emerging technology whose aim is to offload network tasks and infrastructure control plane software from the CPU. Such devices are particularly relevant for TDAQ systems where high rates in the orders of TB/s are produced in large detectors...

113. Test and data acquisition software for CPV-4

Chang Xu

26/04/2024, 09:20

Data Acquisition and Trigger Architectures

Oral presentation

Abstract: Combining 3D vertical integration technology with SOI pixel process, the CPV-4 chip integrates sensing diode and analog front-end functions into the lower-tier chip, while hit information storage and readout functions are implemented in the upper-tier chip. This reduces pixel size and power consumption, thereby enhancing the spatial resolution of the detector. Due to the...

133. Dolosse - A Modern, Scalable, and Extensible Data Acquisition and Management System for Nuclear Physics Experiments

Thabang Mokoena

26/04/2024, 09:40

Data Acquisition and Trigger Architectures

Oral presentation

Dolosse, a project funded by the National Research Foundation, is an innovative open-source Data Acquisition System (DAQ) specifically designed to meet the sophisticated requirements of contemporary nuclear physics research. This framework facilitates a high-throughput, fault-tolerant streaming service capable of handling the 'Big Data' attributes—volume, velocity, and variety—that...

184. The Beam commissioning of SC Cyclotron based Proton Therapy System with fast energy selection and Precise Gantry Positioning

Prof. Tianjue Zhang (China Institute of Atomic Energy)

26/04/2024, 10:00

Real Time Diagnostics, Digital Twin, Control, Monitoring, Safety and Security

Oral presentation

Since 2016, a superconducting cyclotron based proton therapy system has been designed, construction, installation and commissioning at China Institute of Atomic Energy (CIAE). It includes a superconducting cyclotron CYCIAE-230, a beam line with a fast energy selection system, a 360 ° gantry, and a pencil beam scanning nozzle. And there is another beam line for proton irradiation, for example,...

223. CANPS Award: ’50 years of Trigger/DAQ technologies (1970-2020) in HEP and medical field

Mr Patrick Le Du (CEA - IRFU)

26/04/2024, 10:50

114. Study of single-slope ADC using FPGA TDC for streaming readout data acquisition

Tomonori Takahashi (Research Center for Nuclear Physics, Osaka University)

26/04/2024, 11:30

Real Time Diagnostics, Digital Twin, Control, Monitoring, Safety and Security

Oral presentation

The shift of data acquisition systems from traditional hardware-triggered ones to streaming readout ones will be mandatory for near-future experiments. We are developing a streaming data acquisition system and have already established it to measure hit arrival time and charge information using FPGA-based TDC and time-over-threshold (TOT). However, charge measurement with TOT has limited...

24. Control of plasma vertical displacement based on neural network

Ms huihui song (institute of plasma physics)

26/04/2024, 11:50

Real Time Diagnostics, Digital Twin, Control, Monitoring, Safety and Security

Oral presentation

For elongation plasma, the vertical displacement control is essential for the stable operation of tokamak devices. In this paper, a neural network model is used to rapidly detect vertical displacement recognition, and a new vertical displacement control algorithm is built by combining the method of neural network. To reduce latency and provide sufficient computing resources for the neural...