high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Image and Signal Processing

Practically efficient methods for performing bit-reversed permutation in C++11 on the x86-64 architecture

Christian Knauth, Boran Adas, Daniel Whitfield, Xuesong Wang, Lydia Ickler, Tim Conrad, Oliver Serang

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Tags: Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Signal processing

August 8, 2017 by hgpu

A GPU Based Memory Optimized Parallel Method For FFT Implementation

Fan Zhang, Chen Hu, Qiang Yin, Wei Hu

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Tags: CUDA, FFT, Image processing, nVidia, Sensing, Signal processing, Tesla C2070

August 1, 2017 by hgpu

Real-time colouring and filtering with graphics shaders

Dany Vohl, Christopher J. Fluke, David G. Barnes, Amr H. Hassan

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Tags: Algorithms, Astrophysics, Filtering, GLSL, Image processing, nVidia, nVidia GeForce GT 750 M, nVidia GeForce GTX Titan X, nVidia Grid K1, Package, Rendering

July 5, 2017 by hgpu

Synthesis of Embedded Software using Dataflow Schedule Graphs

Abhay Raina

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Tags: Computer science, DSP, nVidia, nVidia GeForce GTX 680, OpenCL, Signal processing, Thesis

July 2, 2017 by hgpu

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

Andreas Palsson

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Tags: Algorithms, Android, Image processing, Java, OpenCL, RenderScript, Thesis

June 25, 2017 by hgpu

On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization

Jose A. Belloch, Jose M. Badia, Francisco D. Igual, Maximo Cobos, Enrique S. Quintana-Orti

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Tags: Algorithms, ARM, nVidia, nVidia GeForce GTX 1080, OpenCL, Signal processing, Tesla K20

June 21, 2017 by hgpu

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Keunwoo Choi, Deokjin Joo, Juho Kim

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Tags: Computer science, CUDA, Deep learning, Keras, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X, Package, Python, Signal processing, Tesla K80, Tesla M60

June 21, 2017 by hgpu

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

Lingyu Duan, Wei Sun, Xinfeng Zhang, Jie Chen, Jianxiong Yin, Simon See, Tiejun Huang, Alex C. Kot, Wen Gao

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Tags: Benchmarking, CUDA, Hybrid computing, Image processing, Neural networks, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, nVidia Tegra TX1, Tesla M40

June 1, 2017 by hgpu

Accelerating Discrete Wavelet Transforms on GPUs

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik

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Tags: ATI, ATI Radeon HD 6970, Computer science, Discrete Wavelet Transform, HLSL, Image processing, nVidia, nVidia GeForce GTX Titan X, OpenCL, Pixel shaders

May 24, 2017 by hgpu

Accelerating Discrete Wavelet Transforms on Parallel Architectures

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Discrete Wavelet Transform, Image processing, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenGL, Performance, Pixel shaders

April 30, 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

Large-scale image analysis using docker sandboxing

B. Sengupta, E. Vazquez, M. Sasdelli, Y. Qian, M. Peniak, L. Netherton, G. Delfino

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia Quadro M 6000

March 14, 2017 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Applications

Practically efficient methods for performing bit-reversed permutation in C++11 on the x86-64 architecture

A GPU Based Memory Optimized Parallel Method For FFT Implementation

Real-time colouring and filtering with graphics shaders

Synthesis of Embedded Software using Dataflow Schedule Graphs

ART vs. NDK vs. GPU acceleration: A study of performance of image processing algorithms on Android

On the Use of a GPU-Accelerated Mobile Device Processor for Sound Source Localization

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing

Accelerating Discrete Wavelet Transforms on GPUs

Accelerating Discrete Wavelet Transforms on Parallel Architectures

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

Large-scale image analysis using docker sandboxing

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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