Multiple Data Set

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The Experts below are selected from a list of 72 Experts worldwide ranked by ideXlab platform

Chick C. Wilson - One of the best experts on this subject based on the ideXlab platform.

Paul F. Henry - One of the best experts on this subject based on the ideXlab platform.

Mark T. Weller - One of the best experts on this subject based on the ideXlab platform.

Kleanthis Psarris - One of the best experts on this subject based on the ideXlab platform.

  • Accelerating Matrix Operations with Improved Deeply Pipelined Vector Reduction
    IEEE Transactions on Parallel and Distributed Systems, 2012
    Co-Authors: Chia-tien Dan Lo, Kleanthis Psarris
    Abstract:

    Many scientific or engineering applications involve matrix operations, in which reduction of vectors is a common operation. If the core operator of the reduction is deeply pipelined, which is usually the case, dependencies between the input Data elements cause Data hazards. To tackle this problem, we propose a new reduction method with low latency and high pipeline utilization. The performance of the proposed design is evaluated for both single Data Set and Multiple Data Set scenarios. Further, QR decomposition is used to demonstrate how the proposed method can accelerate its execution. We implement the design on an FPGA and compare its results to other methods.

  • Multiple Data Set reduction on fpgas
    Field-Programmable Technology, 2010
    Co-Authors: Yigang Tai, Kleanthis Psarris
    Abstract:

    Many scientific or engineering applications perform reduction of Sets of sequential Data streams. If the core operator of the reduction is deeply pipelined, dependencies between the input Data elements cause Data hazards in the pipeline. To tackle this problem, we propose a Multiple Set variable length reduction design with low latency and high pipeline utilization in this paper. We prove the buffer size and execution time bounds, and then show its performance on practical Multiple Data Set scenarios. We apply the proposed method to the Householder QR decomposition and compare its performance to other methods with superior results. The proposed design is implemented on FPGAs with resource usage and performance presented.

  • FPT - Multiple Data Set reduction on FPGAs
    2010 International Conference on Field-Programmable Technology, 2010
    Co-Authors: Yigang Tai, Kleanthis Psarris
    Abstract:

    Many scientific or engineering applications perform reduction of Sets of sequential Data streams. If the core operator of the reduction is deeply pipelined, dependencies between the input Data elements cause Data hazards in the pipeline. To tackle this problem, we propose a Multiple Set variable length reduction design with low latency and high pipeline utilization in this paper. We prove the buffer size and execution time bounds, and then show its performance on practical Multiple Data Set scenarios. We apply the proposed method to the Householder QR decomposition and compare its performance to other methods with superior results. The proposed design is implemented on FPGAs with resource usage and performance presented.

Masaki Horiuchi - One of the best experts on this subject based on the ideXlab platform.

  • EXAFS study of doped ceria using Multiple Data Set fit
    Solid State Ionics, 2005
    Co-Authors: Hiroshi Deguchi, Hiroyuki Yoshida, Toru Inagaki, Masaki Horiuchi
    Abstract:

    Abstract EXAFS analysis was applied to ceria compounds doped with Gd3+, Y3+ and La3+. Although several studies using EXAFS have been reported, their analysis was limited only to the nearest neighbor shell. We analyzed the next nearest neighbor shell using “Multiple Data Set fit” method, where two EXAFS Data Sets of the same sample around Ce4+ and dopant cation were fitted at the same time. Based on the EXAFS results, local structure of the doped ceria compounds was discussed. It was found that Y3+ and La3+ had a strong tendency to get together and formed a dopant-rich cluster including oxygen vacancies, whereas Gd3+ did not gather and distributed randomly in ceria lattice.