Search Results - "Fulp, Megan Hickman"

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  1. 1

    Accelerated dynamic data reduction using spatial and temporal properties by Hickman Fulp, Megan, Fulp, Dakota, Zou, Changfeng, Sanders, Cooper, Biswas, Ayan, Smith, Melissa C., Calhoun, Jon C.

    “…Due to improvements in high-performance computing (HPC) capabilities, many of today’s applications produce petabytes worth of data, causing bottlenecks within…”
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    Journal Article
  2. 2

    Estimating Potential Error in Sampling Interpolation by Fulp, Megan Hickman, Fulp, Dakota, Calhoun, Jon C.

    “…As high-performance computing systems rapidly advance, the volumes of scientific data produced are a prominent issue. Data reduction methods, including…”
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    Conference Proceeding
  3. 3

    Exploring Data Reduction Techniques for Additive Manufacturing Analysis by Nichols, Coleman, Fulp, Megan Hickman, DeBardeleben, Nathan, Calhoun, Jon C.

    “…Additive manufacturing is a rapidly growing area that has the potential to revolutionize society. In order to better understand and improve this process,…”
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    Conference Proceeding
  4. 4

    cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data by Tian, Jiannan, Di, Sheng, Zhao, Kai, Rivera, Cody, Fulp, Megan Hickman, Underwood, Robert, Jin, Sian, Liang, Xin, Calhoun, Jon, Tao, Dingwen, Cappello, Franck

    Published 21-09-2020
    “…Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC applications because it not only significantly reduces storage overhead…”
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    Journal Article
  5. 5

    Dynamic Reduction of Scientific Data Through Spatiotemporal Properties by Hickman Fulp, Megan

    Published 01-01-2021
    “…Improvements in High-Performance Computing (HPC) has enabled researchers to develop more sophisticated simulations and applications which solve previously…”
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    Dissertation
  6. 6
  7. 7

    Combining Spatial and Temporal Properties for Improvements in Data Reduction by Fulp, Megan Hickman, Biswas, Ayan, Calhoun, Jon C.

    “…Due to I/O bandwidth limitations, intelligent in situ data reduction methods are needed to enable post-hoc workflows. Current state-of-the-art sampling methods…”
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    Conference Proceeding