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DLL: A Blazing Fast Deep Neural Network Library

Baptiste Wicht, Jean Hennebert, Andreas Fischer

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 960, Package, Software Engineering

April 15, 2018 by hgpu

Implementing and Evaluating Candidate-Based Invariant Generation

Adam Betts, Nathan Chong, Pantazis Deligiannis, Alastair F. Donaldson, Jeroen Ketema

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Software Engineering

December 10, 2016 by hgpu

Integrating a large-scale testing campaign in the CK framework

Andrei Lascu, Alastair F. Donaldson

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Tags: Computer science, OpenCL, Software Engineering

November 11, 2015 by hgpu

Contract-Based General-Purpose GPU Programming

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package, Software Engineering

October 27, 2014 by hgpu

Teaching Parallel Programming Using Java

Aamir Shafi, Aleem Akhtar, Ansar Javed, Bryan Carpenter

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Tags: Computer science, CUDA, Education, Hadoop, Java, MapReduce, MPI, nVidia, Programming techniques, Software Engineering

October 4, 2014 by hgpu

GPGPU Programming for Games and Science

David H. Eberly

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Tags: Algorithms, Book, Computer science, DirectX, Games, HLSL, Package, Software Engineering

August 21, 2014 by hgpu

Numerical Computations with GPUs

Volodymyr Kindratenko

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Tags: Algorithms, ATI, Book, Computer science, CUDA, Differential equations, FFT, Linear Algebra, Mathematics, Numerical simulation, nVidia, OpenCL, Pseudo-random number generators, Software Engineering

August 13, 2014 by hgpu

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K.A. Hawick, D.P.Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

March 4, 2014 by hgpu

GPU hardware acceleration for industrial applications: using computation to push beyond physical limitations

Mohammadhossein Afrasiabi

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Tags: Algorithms, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 580, nVidia GeForce GTX 590, Rendering, Sensing, Software Engineering, Thesis

December 13, 2013 by hgpu

Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

Cudagrind: A Valgrind Extension for CUDA

Thomas M. Baumann, Jose Gracia

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Tags: Computer science, CUDA, Memory, nVidia, Package, Software Engineering

October 4, 2013 by hgpu

Page 1 of 612 3 4 5...»Last »

OCLADock - OpenCL Accelerated Molecular Docking

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Parallax: A Tool for Automatic Parallelization of Deep Learning Training in Distributed Multi-GPU Environments

Parallax: Automatic Data-Parallel Training of Deep Neural Networks

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image processing and Reconstruction on heterogeneous Devices

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

Spatial: Specify Parameterized Accelerators Through Inordinately Abstract Language

Spatial: A Language and Compiler for Application Accelerators

cuPentBatch: A batched pentadiagonal solver for NVIDIA GPUs

cuPentBatch – A batched pentadiagonal solver for NVIDIA GPUs

LeFlow: Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks

CloudCL: Single-Paradigm Distributed Heterogeneous Computing for Cloud Infrastructures

Calamari: OCR Engine based on OCRopy and Kraken

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

FluidFFT: efficient and easy Fast Fourier Transform for Python

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

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* * *

2018

August

20-21

Guangzhou, China

The 3rd International Conference on Computer Systems and Communication Technology (ICCSCT), 2018

2018

November

02-04

Academic Exchange Center in Ocean University of China, Qingdao, China

The 4th International Conference on Communication and Information Processing (ICCIP), 2018

2018

November

27-30

Hida Takayama, Japan

The Third International Workshop on GPU Computing and AI (GCA), 2018

2018

September

19-21

Nagoya University, Japan

The 5th International Conference on Power and Energy Systems Engineering (CPESE), 2018

2018

September

22-24

MediaCityUK, Salford Quays, Greater Manchester, England

The 10th International Conference on Information Management and Engineering (ICIME), 2018

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high performance computing on graphics processing units: hgpu.org

DLL: A Blazing Fast Deep Neural Network Library

Implementing and Evaluating Candidate-Based Invariant Generation

Integrating a large-scale testing campaign in the CK framework

Contract-Based General-Purpose GPU Programming

Teaching Parallel Programming Using Java

GPGPU Programming for Games and Science

Numerical Computations with GPUs

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

GPU hardware acceleration for industrial applications: using computation to push beyond physical limitations

Multilayered Abstractions for Partial Differential Equations

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Cudagrind: A Valgrind Extension for CUDA

Recent source codes

OCLADock - OpenCL Accelerated Molecular Docking

sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification

Parallax: A Tool for Automatic Parallelization of Deep Learning Training in Distributed Multi-GPU Environments

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image processing and Reconstruction on heterogeneous Devices

Spatial: Specify Parameterized Accelerators Through Inordinately Abstract Language

cuPentBatch: A batched pentadiagonal solver for NVIDIA GPUs

LeFlow: Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks

CloudCL: Single-Paradigm Distributed Heterogeneous Computing for Cloud Infrastructures

Calamari: OCR Engine based on OCRopy and Kraken

FluidFFT: efficient and easy Fast Fourier Transform for Python

Most viewed papers (last 30 days)

Featured events

The 3rd International Conference on Computer Systems and Communication Technology (ICCSCT), 2018

The 4th International Conference on Communication and Information Processing (ICCIP), 2018

The Third International Workshop on GPU Computing and AI (GCA), 2018

The 5th International Conference on Power and Energy Systems Engineering (CPESE), 2018

The 10th International Conference on Information Management and Engineering (ICIME), 2018