high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Real-time PCA calculation for spectral imaging (using SIMD and GP-GPU)

Radovan Josth, Jukka Antikainen, Jiri Havel, Adam Herout, Pavel Zemcik, Markku Hauta-Kasari

Tags: CUDA, Image processing, nVidia

February 2, 2011 by hgpu

Adaptive enhancement and noise reduction in very low light-level video

Henrik Malm, Magnus Oskarsson, Eric Warrant, Petrik Clarberg, Jon Hasselgren, Calle Lejdfors

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Tags: Algorithms, Filtering, Image processing, nVidia, nVidia GeForce 8800

February 2, 2011 by hgpu

Towards Automated Learning of Object Detectors

Marc Ebner

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Tags: Algorithms, Computer vision, Image processing, OpenGL

January 31, 2011 by hgpu

A Novel Monte Carlo Noise Reduction Operator

Ruifeng Xu, Sumanta N. Pattanaik

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Source codes

Tags: ATI, ATI Radeon 9700, Filtering, Image processing, Package

January 30, 2011 by hgpu

Evaluating the Performance of Processing Medical Volume Data on Graphics Hardware

Matthias Raspe, Guido Lorenz and Stefan Muller

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Tags: Computed tomography, CT, Image processing, Medicine, MRI, nVidia, nVidia GeForce 8800 GTS

January 27, 2011 by hgpu

Weak execution ordering – exploiting iterative methods on many-core GPUs

Jianmin Chen, Zhuo Huang, Feiqi Su, Jih-Kwon Peir, Jeff Ho, Lu Peng

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Tags: Computer vision, CUDA, Image processing, nVidia, Partial differential equations, PDEs, Tesla C1060

January 26, 2011 by hgpu

Correlating Radio Astronomy Signals with Many-Core Hardware

Rob van Nieuwpoort, John Romein

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Tags: Astrophysics, ATI, ATI CAL, ATI Radeon HD 4870, ATI Stream, Brook, Cell processor, CUDA, nVidia, OpenCL, Performance, Physics, Signal processing, Tesla C1060

January 26, 2011 by hgpu

Sparse regularization in MRI iterative reconstruction using GPUs

Yue Zhuo, Bradley Sutton, Xiao-Long Wu, Justin Haldar, Wen-mei Hwu, Zhipei Liang

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Y. Zhuo, X-L. Wu, J. P. Haldar, W-M. W. Hwu, Z-P. Liang, and B. P. Sutton

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, Tesla S1070

January 24, 2011 by hgpu

Accelerating iterative field-compensated MR image reconstruction on GPUs

Yue Zhuo, Xiao-Long Wu, Justin P. Haldar, Wen-mei Hwu, Zhi-pei Liang, Bradley P. Sutton

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Tags: Conjugate gradient solver, CUDA, Image processing, Image reconstruction, Medicine, MRI, nVidia, nVidia GeForce GTX 280

January 24, 2011 by hgpu

Genetic programming on GPUs for image processing

Simon Harding and Wolfgang Banzhaf

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Tags: Computer science, DirectX, Filtering, Genetic programming, Image processing, nVidia, nVidia GeForce 8800 GTX

January 23, 2011 by hgpu

Simultaneous and fast 3D tracking of multiple faces in video by GPU-based stream processing

Oscar Mateo Lozano, Kazuhiro Otsuka

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Tags: CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, Particle filtering, Video tracking

January 20, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Real-time PCA calculation for spectral imaging (using SIMD and GP-GPU)

Adaptive enhancement and noise reduction in very low light-level video

Towards Automated Learning of Object Detectors

A Novel Monte Carlo Noise Reduction Operator

Evaluating the Performance of Processing Medical Volume Data on Graphics Hardware

Weak execution ordering – exploiting iterative methods on many-core GPUs

Correlating Radio Astronomy Signals with Many-Core Hardware

Sparse regularization in MRI iterative reconstruction using GPUs

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Accelerating iterative field-compensated MR image reconstruction on GPUs

Genetic programming on GPUs for image processing

Simultaneous and fast 3D tracking of multiple faces in video by GPU-based stream processing

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)