high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Image and Signal Processing

GPU-Friendly Local Regression for Voice Conversion

Taylor Berg-Kirkpatrick, Dan Klein

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Tags: Acoustics, CUDA, nVidia, Signal processing, Tesla K40

June 24, 2015 by hgpu

DCT-JPEG Image Coding Based on GPU

Rongyang Shan, Chengyou Wang, Wei Huang, Xiao Zhou

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 480

June 24, 2015 by hgpu

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Lucas Benedicic

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Tags: Algorithms, Cellular automata, Metaheuristics, nVidia, nVidia GeForce GTX 660 Ti, OpenCL, Package, Signal processing, Thesis

June 22, 2015 by hgpu

Parallelization of DIRA and CTmod using OpenMP and OpenCL

Alexander Ortenberg

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Tags: AMD Radeon R7 260, ATI, Computed tomography, CT, Image processing, Image reconstruction, Intel Xeon Phi, Medicine, OpenCL, OpenMP, Thesis, Tomography

June 16, 2015 by hgpu

A GPU vs CPU performance evaluation of an experimental video compression algorithm

Stamos Katsigiannis, Vasilis Dimitsas, Dimitris Maroulis

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, Tesla C2070, Video encoding

June 14, 2015 by hgpu

Fast algorithms and efficient GPU implementations for the Radon transform and the back-projection operator represented as convolution operators

Fredrik Andersson, Marcus Carlsson, Viktor V. Nikitin

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Tags: Algorithms, CUDA, FFT, Image processing, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 770, Radon transform

June 5, 2015 by hgpu

Research on the fast Fourier transform of image based on GPU

Feifei Shen, Zhenjian Song, Congrui Wu, Jiaqi Geng, Qingyun Wang

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Tags: Algorithms, FFT, Image processing, Mathematical Software, nVidia, nVidia GeForce 8600 GT

June 1, 2015 by hgpu

Efficient FFT mapping on GPU for radar processing application: modeling and implementation

Mohamed Amine Bergach, Emilien Kofman, Robert de Simone, Serge Tissot, Michel Syska

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Tags: FFT, GPGPU, Intel HD 5200, Intel HD Graphics 4000, OpenCL, SAR

June 1, 2015 by Aminems

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

Johann Hauswald, Yiping Kang, Michael A. Laurenzano, Quan Chen, Cheng Li, Trevor Mudge, Ronald G. Dreslinski, Jason Mars, Lingjia Tang

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Tags: CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K40

May 25, 2015 by hgpu

On the Choice of Tensor Estimation for Corner Detection, Optical Flow and Denoising

Freddie Astrom, Michael Felsberg

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 670, OpenGL, Optical flow

May 25, 2015 by hgpu

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, Thomas Brox

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Tags: CNN, Computer science, CUDA, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia GeForce GTX Titan, Package

May 20, 2015 by hgpu

Adaptive discrete cosine transform-based image compression method on a heterogeneous system platform using Open Computing Language

Nasser Alqudami, Shin-Dug Kim

Tags: Algorithms, Compression, Heterogeneous systems, Image processing, OpenCL

May 15, 2015 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

GPU-Friendly Local Regression for Voice Conversion

DCT-JPEG Image Coding Based on GPU

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Parallelization of DIRA and CTmod using OpenMP and OpenCL

A GPU vs CPU performance evaluation of an experimental video compression algorithm

Fast algorithms and efficient GPU implementations for the Radon transform and the back-projection operator represented as convolution operators

Research on the fast Fourier transform of image based on GPU

Efficient FFT mapping on GPU for radar processing application: modeling and implementation

DjiNN and Tonic: DNN as a Service and Its Implications for Future Warehouse Scale Computers

On the Choice of Tensor Estimation for Corner Detection, Optical Flow and Denoising

U-Net: Convolutional Networks for Biomedical Image Segmentation

Adaptive discrete cosine transform-based image compression method on a heterogeneous system platform using Open Computing Language

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Most viewed papers (last 30 days)