high performance computing on graphics processing units: hgpu.org

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Accelerating digital forensic searching through GPGPU parallel processing techniques

Ethan Bayne

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Tags: Computer science, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970 M, nVidia GeForce GTX 980, nVidia GeForce GTX 980 Ti, OpenCL, Thesis

August 14, 2017 by xhgpu

CLBlast: A Tuned OpenCL BLAS Library

Cedric Nugteren

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Tags: AMD Radeon R9 M370X, ARM, ATI, BLAS, Computer science, Intel HD 5100, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan X, OpenCL, Package

May 18, 2017 by hgpu

Investigation of heterogeneous computing through novel parallel programming platforms

Andrei-Alexandru Dafinoiu

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Tags: ARM, ATI, ATI Radeon HD 6450, ATI Radeon HD 6570, Computer science, FPGA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, SoC, Thesis

April 17, 2017 by hgpu

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Takuya Matsumoto, Kiminori Matsuzaki

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Tags: Computer science, CUDA, Haskell, Image processing, MRI, nVidia, nVidia GeForce GTX 750 Ti

April 3, 2017 by hgpu

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Pedro Miguel Marques Pereira

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, ATI Radeon HD 7970, Compression, Computer science, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570 M, nVidia GeForce GTX 680, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan Black, nVidia Jetson TK1, OpenCL, OpenMP, Thesis

November 30, 2016 by hgpu

GPU Concurrency Choices in Graph Analytics

Masab Ahmad, Omer Khan

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970, OpenCL

October 8, 2016 by hgpu

Finite Element Integration with Quadrature on the GPU

Matthew G. Knepley, Karl Rupp, Andy R. Terrel

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Tags: AMD FirePro W9100, ATI, Computer science, Differential equations, Mathematical Software, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 750 Ti, OpenCL, Partial differential equations, PDEs, Tesla K20

July 16, 2016 by hgpu

Efficient High-Speed WPA2 Brute Force Attacks using Scalable Low-Cost FPGA Clustering

Markus Kammerstetter, Markus Muellner, Daniel Burian, Christian Kudera, Wolfgang Kastner

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 770, nVidia GRID K520, Security

May 28, 2016 by hgpu

Improving GPU Performance: Reducing Memory Conflicts and Latency

Gert-Jan van den Braak

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Tags: Benchmarking, Computer science, CUDA, GPGPU-sim, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 470, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Thesis

May 11, 2016 by hgpu

GPU Multisplit

Saman Ashkiani, Andrew Davidson, Ulrich Meyer, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 750 Ti, Tesla K40

January 22, 2016 by hgpu

A time-energy performance analysis of MapReduce on heterogeneous systems with GPUs

Dumitrel Loghin, Lavanya Ramapantulu, Oana Barbu, Yong Meng Teo

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 750 Ti, nVidia Jetson TK1

December 22, 2015 by hgpu

Adaptive and Transparent Cache Bypassing for GPUs

Ang Li, Gert-Jan van den Braak, Akash Kumar, Henk Corporaal

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Tags: Benchmarking, cache, Computer science, Memory, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 570, nVidia GeForce GTX 690, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 980, Performance, PTX, Tesla K40, Tesla K80

September 24, 2015 by hgpu

Page 1 of 212 »

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

See all packages

* * *

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

Accelerating digital forensic searching through GPGPU parallel processing techniques

CLBlast: A Tuned OpenCL BLAS Library

Investigation of heterogeneous computing through novel parallel programming platforms

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

GPU Concurrency Choices in Graph Analytics

Finite Element Integration with Quadrature on the GPU

Efficient High-Speed WPA2 Brute Force Attacks using Scalable Low-Cost FPGA Clustering

Improving GPU Performance: Reducing Memory Conflicts and Latency

GPU Multisplit

A time-energy performance analysis of MapReduce on heterogeneous systems with GPUs

Adaptive and Transparent Cache Bypassing for GPUs

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