Results 11 to 20 of about 48,067 (311)
Fast reconstruction of X-ray dynamic micro-CT based on GPU parallel computing
He jishu, 2021 BackgroundMassive projection data are produced by user experiments with the X-ray dynamic micro-computed tomography (CT) method on the X-ray imaging beamline at Shanghai synchrotron radiation facility (SSRF).
ZHANG Yuan +5 more
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WTF, GPU! computing twitter's who-to-follow on the GPU [PDF]
Proceedings of the second ACM conference on Online social networks, 2014 In this paper, we investigate the potential of GPUs for performing link structure analysis of social graphs. Specifically, we implement Twitter's WTF ("Who to Follow") recommendation system on a single GPU. Our implementation shows promising results on moderate-sized social graphs. It can return the top-K relevant users for a single user in 172 ms when
Geil, Afton +2 more
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GPU@BU—GPU computing at Boston University
, 2012 A short history of GPU computing at Boston University, made into a handout for the BU booth at the Supercomputing Conference, Salt Lake City, November 2012.
Lorena A. Barba (97553)
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ISPRS International Journal of Geo-Information, 2023 Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it is computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges.
Guiming Zhang, Jin Xu
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Computing Treewidth on the GPU
CoRR, 2017 We present a parallel algorithm for computing the treewidth of a graph on a GPU. We implement this algorithm in OpenCL, and experimentally evaluate its performance. Our algorithm is based on an $O^*(2^{n})$-time algorithm that explores the elimination orderings of the graph using a Held-Karp like dynamic programming approach.
Tom C. van der Zanden +1 more
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GPU Computing with Python: Performance, Energy Efficiency and Usability [PDF]
, 2020 In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU).
Holm, Håvard Heitlo +5 more
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GPU computing for systems biology [PDF]
Briefings in Bioinformatics, 2010 The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate ...
L. Dematte, Prandi, Davide
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GPU computing performance analysis on matrix multiplication
The Journal of Engineering, 2019 The machine learning has been widely used in intelligent data mining. The high-computational complexity of machine learning and huge data volume present challenges to computing platforms.
Zhibin Huang +3 more
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GPU acceleration for statistical gene classification [PDF]
, 2010 The use of Bioinformatic tools in routine clinical diagnostics is still facing a number of issues. The more complex and advanced bioinformatic tools become, the more performance is required by the computing platforms.
Stefano Di Carlo +7 more
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GPU Concurrency: Weak Behaviours and Programming Assumptions [PDF]
, 2014 Concurrency is pervasive and perplexing, particularly on graphics processing units (GPUs). Current specifications of languages and hardware are inconclusive; thus programmers often rely on folklore assumptions when writing software.
Alastair F. Donaldson +23 more
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