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FLASH: Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search

Yiqiu Wang, Anshumali Shrivastava, Junghee Ryu

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Tags: Algorithms, Computer science, Hashing, Machine learning, Nearest neighbour, nVidia, OpenCL, OpenMP, Tesla P100

September 7, 2017 by hgpu

Multi-Tasking Scheduling for Heterogeneous Systems

Yuan Wen

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 780, OpenCL, Task scheduling, Thesis

September 7, 2017 by hgpu

Benchmarking Harp-DAAL: High Performance Hadoop on KNL Clusters

Langshi Chen, Bo Peng, Bingjing Zhang, Tony Liu, Yiming Zou, Lei Jiang, Robert Henschel, Craig Stewart, Zhang Zhang, Emily Mccallum, Zahniser Tom, Omer Jon, Judy Qiu

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Tags: Benchmarking, big data, Computer science, Intel Xeon Phi, Java, Machine learning, MapReduce, MPI, Package, Performance

September 3, 2017 by hgpu

Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes

Yuriy Kochura, Sergii Stirenko, Oleg Alienin, Michail Novotarskiy, Yuri Gordienko

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Tags: Computer science, CUDA, Deep learning, Image recognition, Java, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Performance, TensorFlow, Tesla K40

September 3, 2017 by hgpu

Scaling Deep Learning on GPU and Knights Landing clusters

Yang You, Aydin Buluc, James Demmel

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Tags: Cloud, Computer science, Deep learning, GPU cluster, Intel Xeon Phi, Machine learning, Neural networks, nVidia, Package, PC cluster, Tesla K80, Tesla M100

August 17, 2017 by hgpu

GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators

Zhen Xu, Xuhao Chen, Jie Shen, Yang Zhang, Cheng Chen, Canqun Yang

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Tags: Benchmarking, Computer science, CUDA, Graph theory, Machine learning, nVidia, Package, Tesla K40

August 17, 2017 by hgpu

Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach

Merijn Verstraaten, Ana Lucia Varbanescu, Cees de Laat

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Graph theory, Machine learning, nVidia, nVidia GeForce GTX Titan X, Package

August 8, 2017 by hgpu

Scalability Study of Deep Learning Algorithms in High Performance Computer Infrastructures

Francesc Sastre Cabot

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, Tesla K80, Tesla M2090, Thesis

July 22, 2017 by hgpu

A Comparison of Support Vector Machines Training GPU-Accelerated Open Source Implementations

Jan Vanek, Josef Michalek, Josef Psutka

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Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

July 22, 2017 by hgpu

Automatically Selecting Profitable Thread Block Sizes Using Machine Learning

Tiffany A. Connors

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Tags: Computer science, CUDA, Machine learning, nVidia, Performance, Tesla K40, Thesis

July 22, 2017 by hgpu

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

Wajih Halim Boukaram, George Turkiyyah, Hatem Ltaief, David E. Keyes

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Numerical Analysis, nVidia, Tesla P100

July 19, 2017 by hgpu

Benchmarking Data Analysis and Machine Learning Applications on the Intel KNL Many-Core Processor

Chansup Byun, Jeremy Kepner, William Arcand, David Bestor, Bill Bergeron, Vijay Gadepally, Michael Houle, Matthew Hubbell, Michael Jones, Anna Klein, Peter Michaleas, Lauren Milechin, Julie Mullen, Andrew Prout, Antonio Rosa, Siddharth Samsi, Charles Yee, Albert Reuther

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Tags: Benchmarking, Caffe, Computer science, Deep learning, Intel Xeon Phi, Machine learning, Performance

July 14, 2017 by hgpu