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Träfflista för sökning "WFRF:(Liu Zhenan) "

Sökning: WFRF:(Liu Zhenan)

  • Resultat 1-7 av 7
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1.
  • Liu, Ming, et al. (författare)
  • A High-End Reconfigurable Computation Platform for Nuclear and Particle Physics Experiments
  • 2011
  • Ingår i: Computing in science & engineering (Print). - 1521-9615 .- 1558-366X. ; 13:2, s. 52-63
  • Tidskriftsartikel (refereegranskat)abstract
    • A high-performance computation platform based on field-programmable gate arrays targets nuclear and particle physics experiment applications. The system can be constructed or scaled into a supercomputer-equivalent size for detector data processing by inserting compute nodes into advanced telecommunications computing architecture (ATCA) crates. Among the case study results are that one ATCA crate can provide a computation capability equivalent to hundreds of commodity PCs for Hades online particle track reconstruction and Cherenkov ring recognition.
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2.
  • Liu, Ming, et al. (författare)
  • ATCA-based Computation Platform for Data Acquisition and Triggering in Particle Physics Experiments
  • 2008
  • Ingår i: 2008 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE AND LOGIC APPLICATIONS, VOLS 1 AND 2. ; , s. 287-292
  • Konferensbidrag (refereegranskat)abstract
    • An ATCA-based computation platform for data acquisition and trigger applications in nuclear and particle physics experiments has been developed. Each Compute Node (CN) which appears as a Field Replaceable Unit (FRU) in an ATCA shelf, features 5 Xilinx Virtex-4 FX60 FPGAs and up to 10 GBytes DDR2 memory. Connectivity is provided with 8 optical links and 5 Gigabit Ethernet ports, which are mounted on each board to receive data from detectors and forward results to outer shelves or PC farms with attached mass storage. Fast point-to-point on-board interconnections between FPGAs as well as the full-mesh shelf backplane provide flexibility and high bandwidth to partition algorithms and correlate results among them. The system represents a highly reconfigurable and scalable solution for multiple applications.
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3.
  • Liu, Ming, et al. (författare)
  • Hardware/Software co-design of a general-purpose computation platform in particle physics
  • 2007
  • Ingår i: ICFPT 2007. - 9781424414710 ; , s. 177-183
  • Konferensbidrag (refereegranskat)abstract
    • In this paper we present a hardware/software co-design based computation platform for online data processing in particle physics experiments. Our goal is to ease and accelerate the development and make it universal and scalable for multiple applications, on the premise of guaranteeing high communicating and processing capabilities. The entire computation network consists of quite a few interconnected compute nodes, each of which has multiple FPGAs to implement specific algorithms for data processing. High-speed communication features including RocketIO multi-gigabit transceiver and Gigabit Ethernet are supported by FPGAs to construct internal and external connections. An embedded Linux operating system is fitted on the PowerPC CPU core inside the Xilinx Virtex-4 FX FPGA. Thus programmers can access hardware resources via device drivers and write application programs to manage the system from the high level. Furthermore measurements have been executed using the development board to investigate both communicating and processing performances of the system. Results show that the computation platform is able to communicate at a UDP/IP data rate of around 400 Mbps per Ethernet link, and the event selection engine could process an event rate of 25%.
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4.
  • Liu, Ming, et al. (författare)
  • Trigger algorithm development on FPGA-based Compute Nodes
  • 2009
  • Ingår i: 2009 16th IEEE-NPSS Real Time Conference. - New York : IEEE. - 9781424457960 ; , s. 478-484
  • Konferensbidrag (refereegranskat)abstract
    • Based on the ATCA computation architecture and Compute Nodes (CN), investigation and implementation work has been being executed for HADES and PANDA trigger algorithms. We present our designs for HADES track reconstruction processing, Cherenkov ring recognition, Time-Of-Flight processing, electromagnetic shower recognition.. and the PANDA straw tube tracking algorithm. They will appear as co-processors in the uniform system design to undertake the detector-specific computing. The algorithm principles will be explained and hardware designs are described in the paper. The current progress reveals the feasibility to implement these algorithms on FPGAs. Also experimental results demonstrate the performance speedup when compared to alternative software solutions, as well as the potential capability of high-speed parallel/pipelined processing in Data Acquisition and Trigger systems.
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5.
  • Wang, Qiang, et al. (författare)
  • Hardware/Software Co-design of an ATCA-based Computation Platform for Data Acquisition and Triggering
  • 2009
  • Ingår i: 16th IEEE NPSS Real Time Conference. - 9781424457960 ; , s. 485-489
  • Konferensbidrag (refereegranskat)abstract
    • An ATCA-based computation platform for data acquisition and trigger(TDAQ) applications has been developed for multiple future projects such its PANDA. HADES, and BESIII. Each Compute Node (CN) appears as one (if the fourteen Field Replaceable Units (FRU) in an ATCA shelf, which in total features a high performance of 1890 Clips inter-FPGA on-board channels, 1456 Gbps inter-board backplane connections, 728 Gbps full-duplex optical links, 70 Gbps Ethernet. 140 GBytes DDR2 SDRAM. and all computing resources of 70 Xilinx Virtex-4 FX60 FPGAs. Corresponding to (the system architecture, a hardware/software co-design approach is proposed to ease and accelerate the development for different experiments. In the uniform system design. application-specific computation is to be implemented as customized hardware co-processors, while the embedded PowerPC processor takes charge of flexible slow controls and transmission protocol processing.
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6.
  • Fan, Zhenan, et al. (författare)
  • Improving Fairness for Data Valuation in Horizontal Federated Learning
  • 2022
  • Ingår i: 38th IEEE International Conference on Data Engineering, ICDE 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 2440-2453
  • Konferensbidrag (refereegranskat)abstract
    • Federated learning is an emerging decentralized machine learning scheme that allows multiple data owners to work collaboratively while ensuring data privacy. The success of federated learning depends largely on the participation of data owners. To sustain and encourage data owners' participation, it is crucial to fairly evaluate the quality of the data provided by the data owners as well as their contribution to the final model and reward them correspondingly. Federated Shapley value, recently proposed by Wang et al. [Federated Learning, 2020], is a measure for data value under the framework of federated learning that satisfies many desired properties for data valuation. However, there are still factors of potential unfairness in the design of federated Shapley value because two data owners with the same local data may not receive the same evaluation. We propose a new measure called completed federated Shapley value to improve the fairness of federated Shapley value. The design depends on completing a matrix consisting of all the possible contributions by different subsets of the data owners. It is shown under mild conditions that this matrix is approximately low-rank by leveraging concepts and tools from optimization. Both theoretical analysis and empirical evaluation verify that the proposed measure does improve fairness in many circumstances.
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7.
  • Zhang, Man, et al. (författare)
  • The First ICB Competition on Iris Recognition
  • 2014
  • Ingår i: 2014 IEEE International Joint Conference on Biometrics (IJCB). - Piscataway, NJ : IEEE Press. - 9781479935840
  • Konferensbidrag (refereegranskat)abstract
    • Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB∗ Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database (e.g. CASIA-Iris-Thousand [3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0.0001 are taken to rank the submitted algorithms. © 2014 IEEE.
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  • Resultat 1-7 av 7

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