high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

GPU Acceleration of Image Convolution using Spatially-varying Kernel

Steven Hartung, Hemant Shukla, J. Patrick Miller, Carlton Pennypacker

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Tags: Algorithms, Astrophysics, CUDA, FFT, Image processing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 465

September 27, 2012 by hgpu

Sound Speed Optimization Using Image Texture on CUDA

Xingwu He, Huaguo Yin, Honglin Zhou, Xia Zhang

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 560, Optimization, Ultrasound

September 24, 2012 by hgpu

Computer Vision Application in Graphic Processors

Chouchene Marwa, Sayadi Fatma, Tourki Rached

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Tags: Computer science, Computer vision, GLSL, Image processing, nVidia, nVidia GeForce GT 310 M, OpenGL

September 23, 2012 by hgpu

Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines

George Teodoro, Tony Pan, Tahsin Kurc, Jun Kong, Lee Cooper, Joel Saltz

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Tags: Algorithms, Computer science, CUDA, Distance transform, Heterogeneous systems, Image processing, nVidia, Tesla M2090

September 18, 2012 by hgpu

NT-SIM: A Co-Simulator for Networked Signal Processing Applications

Stephen Won, Chung-Ching Shen, Shuvra S. Bhattacharyya

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Tags: CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, Signal processing

September 15, 2012 by hgpu

Fast Determination of the Number of Endmembers for Real-Time Hyperspectral Unmixing on GPUs

Sergio Sanchez, Antonio Plaza

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 580

September 12, 2012 by hgpu

CuNeuQuant: A CUDA Implementation of the NeuQuant Image Quantization Algorithm

David Bottisti, Liuva Mendez, Damian Dechev

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Tags: Algorithms, Computer vision, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce 9800 GTX, Package

September 10, 2012 by hgpu

Mastering Software Variant Explosion for GPU Accelerators

Richard Membarth, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia Quadro FX 5800, OpenCL, Package, Tesla C2050

September 8, 2012 by hgpu

High Performance Parallel Implementation of Compressive Sensing SAR Imaging

Jihua Tian, Jinping Sun, Yuxi Zhang, Najeeb Ahmad

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Tags: CUDA, Image processing, nVidia, Sensing, Tesla C1060

September 7, 2012 by hgpu

Accelerating and Characterizing Seam Carving Using a Heterogeneous CPU-GPU System

Ronald Duarte, Resit Sendag

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Tags: CUDA, Image processing, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 580

September 5, 2012 by hgpu

Performance Analysis on Several GPU Architectures of an Algorithm for Noise Removal

M. G. Sanchez, V. Vidal, J. Bataller, G. Verdu

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GT 120, Signal denoising, Tesla M2050

September 1, 2012 by hgpu

Intelligent Edge Detection using a CUDA Simulator of Multilayer Neural Network Based on Multi-Valued Neurons

Jeff Wilson, Igor Aizenberg

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Tags: CUDA, Edge detection, Image processing, Neural networks, nVidia, nVidia GeForce GTX 450, nVidia GeForce GTX 550 Ti

August 28, 2012 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 Acceleration of Image Convolution using Spatially-varying Kernel

Sound Speed Optimization Using Image Texture on CUDA

Computer Vision Application in Graphic Processors

Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines

NT-SIM: A Co-Simulator for Networked Signal Processing Applications

Fast Determination of the Number of Endmembers for Real-Time Hyperspectral Unmixing on GPUs

CuNeuQuant: A CUDA Implementation of the NeuQuant Image Quantization Algorithm

Mastering Software Variant Explosion for GPU Accelerators

High Performance Parallel Implementation of Compressive Sensing SAR Imaging

Accelerating and Characterizing Seam Carving Using a Heterogeneous CPU-GPU System

Performance Analysis on Several GPU Architectures of an Algorithm for Noise Removal

Intelligent Edge Detection using a CUDA Simulator of Multilayer Neural Network Based on Multi-Valued Neurons

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

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