high performance computing on graphics processing units: hgpu.org

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Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

Ander Biguri, Reuben Lindroos, Robert Bryll, Hossein Towsyfyan, Hans Deyhle, Richard Boardman, Mark Mavrogordato, Manjit Dosanjh, Steven Hancock, Thomas Blumensath

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Tags: Algorithms, Computed tomography, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, Package

May 12, 2019 by hgpu

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Sangkyun Lee, Jeonghyun Lee

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Tags: Algorithms, ARM, Compression, Computer science, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Package

May 5, 2019 by hgpu

Wasserstein-Fisher-Rao Document Distance

Zihao Wang, Datong Zhou, Yong Zhang, Hao Wu, Chenglong Bao

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Tags: Computer science, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 1080 Ti

April 28, 2019 by hgpu

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

Ao Ren, Tianyun Zhang, Shaokai Ye, Jiayu Li, Wenyao Xu, Xuehai Qian, Xue Lin, Yanzhi Wang

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Tags: Caffe, Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla P100

January 6, 2019 by hgpu

A Study on the Acceleration of Arrival Curve Construction and Regular Specification Mining using GPUs

Nirmal Joshi Benann Rajendra

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Tags: AMD Radeon R9 390X, ATI, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080 Ti, OpenCL, Thesis

December 30, 2018 by hgpu

Performance Analysis of a Stereo Matching Implementation in OpenCL

Stephan Rotheneder

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 750 Ti, nVidia Quadro 1000 M, OpenCL, Stereo vision

December 16, 2018 by hgpu

A Framework for Fast and Efficient Neural Network Compression

Hyeji Kim, Muhammad Umar Karim, Chong-Min Kyung

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Tags: ARM, Caffe, Compression, Computational Complexity, Computer science, Computer vision, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti

December 9, 2018 by hgpu

Accelerating Low-End Edge Computing with Cross-Kernel Functionality Abstraction

Chao Wu, Yaoxue Zhang, Yuezhi Zhou, Qiushi Li

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance

November 18, 2018 by hgpu

A Comparative Measurement Study of Deep Learning as a Service Framework

Yanzhao Wu, Ling Liu, Calton Pu, Wenqi Cao, Semih Sahin, Wenqi Wei, Qi Zhang

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Tags: Caffe, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Tesla M60, Theano

November 3, 2018 by hgpu

OpenCL Performance Prediction using Architecture-Independent Features

Beau Johnston, Greg Falzon, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon R9 290X, AMD Radeon R9 295X2, AMD Radeon RX 480, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, OpenCL, Package, performance portability, Tesla K20, Tesla K40

November 3, 2018 by hgpu

Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms

Andreea Anghel, Nikolaos Papandreou, Thomas Parnell, Alessandro De Palma, Haralampos Pozidis

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Tags: Algorithms, Bayesian, Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti

September 16, 2018 by hgpu

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

Christoph Wick, Christian Reul, Frank Puppe

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Tags: Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Python, TensorFlow

July 7, 2018 by hgpu

HPCToolkit

Refining HPCToolkit for application performance analysis at exascale

Open Catalog of Best Practices for Modernization and Optimization

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Noarr Structures

Abstractions for C++ code optimizations in parallel high-performance applications

$3D-fractal-generators$

HiCCL: A hierarchical collective communications library with portable optimizations

HiCCL: A Hierarchical Collective Communication Library

See all packages

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high performance computing on graphics processing units: hgpu.org

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Wasserstein-Fisher-Rao Document Distance

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

A Study on the Acceleration of Arrival Curve Construction and Regular Specification Mining using GPUs

Performance Analysis of a Stereo Matching Implementation in OpenCL

A Framework for Fast and Efficient Neural Network Compression

Accelerating Low-End Edge Computing with Cross-Kernel Functionality Abstraction

A Comparative Measurement Study of Deep Learning as a Service Framework

OpenCL Performance Prediction using Architecture-Independent Features

Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

Recent source codes

HPCToolkit

Open Catalog of Best Practices for Modernization and Optimization

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

GPU-Smash: Compression abstraction library

Noarr Structures

3D-fractal-generators

SyncPerformance

VerCors: a verification toolset for verifying parallel and concurrent software

HiCCL: A hierarchical collective communications library with portable optimizations

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