high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing

Zhou Haifang, Xu Rulin, Jiang Jingfei

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Tags: CUDA, Image processing, Image registration, nVidia, Sensing, Tesla M2050, Wavelet

November 30, 2013 by hgpu

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

Achille Peternier, Marco Defilippi, Paolo Pasquali, Alessio Cantone, Rolf Krause, Raffaele Vitulli, Fumitaka Ogushi, Alberto Meroni

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenCL, Tesla C2050

November 27, 2013 by hgpu

Dynamic Partitioning-based JPEG Decompression on Heterogeneous Multicore Architectures

Wasuwee Sodsong, Jingun Hong, Seongwook Chung, Shin-Dug Kim, Bernd Burgstaller

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Tags: Compression, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 680, OpenCL, Performance

November 23, 2013 by hgpu

An improved parallel contrast-aware halftoning

Ling-yue Liu, Wei Chen, Tien-tsin Wong, Wen-ting Zheng, Wei-dong Geng

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

November 22, 2013 by hgpu

GPGPU-accelerated Interesting Interval Discovery and other Computations on GeoSpatial Datasets – A Summary of Results

Sushil K. Prasad, Shashi Shekhar, Michael McDermott, Xun Zhou, Michael Evans, Satish Puri

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Tags: Algorithms, CUDA, Earth and Space Sciences, Image processing, nVidia, nVidia GeForce GTX 480, OpenGL

November 17, 2013 by hgpu

Implementation of Diamond Search Algorithm Using Parallel Processing Architecture

K. Shuma Roshini, M. Tejaswi

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GT 610, Video encoding

November 17, 2013 by hgpu

Parallel Implementation of Color Based Image Retrieval Using CUDA on the GPU

Hadis Heidari, Abdolah Chalechale, Alireza Ahmadi Mohammadabadi

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GT 610 M

November 17, 2013 by hgpu

SAGE: Self-Tuning Approximation for Graphics Engines

Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi, Amir Hormati, Scott Mahlke

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Tags: Algorithms, Code generation, Compilers, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 560, Performance

November 14, 2013 by hgpu

Designing Scientific Applications on GPUs

Raphael Couturier

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Tags: Book, Computer science, CUDA, Factorization, Fluid simulation, Image processing, Mathematics, nVidia, Physics, Tutorial

November 13, 2013 by hgpu

Optimization of real-time ultrasound PCIe data streaming and OpenCL processing for SAFT imaging

M. Walczak, M. Lewandowski, N. Zolek

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Tags: FPGA, Image processing, Image reconstruction, nVidia, nVidia Quadro K5000, OpenCL, Ultrasound

November 10, 2013 by hgpu

Performance Analysis of Sobel Edge Detection Filter on GPU using CUDA & OpenGL

Khyati Shah

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GT 130, OpenGL, Performance

November 10, 2013 by hgpu

Implementation of Spectral Angle Mapper (SAM) Algorithm on a Graphic processing unit (GPU)

Balaji Vengatesh M.

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 560

November 10, 2013 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

Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing

Performance Analysis of GPU-based SAR and Interferometric SAR image processing

Dynamic Partitioning-based JPEG Decompression on Heterogeneous Multicore Architectures

An improved parallel contrast-aware halftoning

GPGPU-accelerated Interesting Interval Discovery and other Computations on GeoSpatial Datasets – A Summary of Results

Implementation of Diamond Search Algorithm Using Parallel Processing Architecture

Parallel Implementation of Color Based Image Retrieval Using CUDA on the GPU

SAGE: Self-Tuning Approximation for Graphics Engines

Designing Scientific Applications on GPUs

Optimization of real-time ultrasound PCIe data streaming and OpenCL processing for SAFT imaging

Performance Analysis of Sobel Edge Detection Filter on GPU using CUDA & OpenGL

Implementation of Spectral Angle Mapper (SAM) Algorithm on a Graphic processing unit (GPU)

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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