high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Two Stage Data Mining Technique for Fast Monsoon Onset Prediction

Dinu John, K. K. Sindhu, B. B. Meshram

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Tags: CUDA, Data mining, Earth and Space Sciences, Image processing, nVidia, Weather prediction

July 3, 2012 by hgpu

API-Compiling for Image Hardware Accelerators

Fabien Coelho, Francois Irigoin

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Tags: Code generation, Image processing, nVidia, nVidia GeForce 9300 GE, OpenCL

July 2, 2012 by hgpu

CUDA-accelerated Hierarchical K-means

Che-Chun Lee, Kuan-Yu Chu

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

July 1, 2012 by hgpu

A Parallel Image Segmentation Algorithm on GPUs

P. N. Happ, R. Q. Feitosa, C. Bentes, R. Farias

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Tags: CUDA, Image processing, nVidia, nVidia GeForce 9600 GT, Tesla C1060

June 29, 2012 by hgpu

GPU Computing: Image Convolution

Jan Novak, Anton Kaplanyan, Gabor Liktor, Carsten Dachsbacher

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Tags: Education, Image processing, OpenCL, Package

June 20, 2012 by hgpu

Point to point processing of digital images using parallel computing

Eric Olmedo, Jorge de la Calleja, Antonio Benitez, Ma. Auxilio Medina

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GT 430

June 10, 2012 by hgpu

Fast Morphological Image Processing Open-Source Extensions for GPU processing with CUDA

Matthew J. Thurley, Victor Danell

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 470, Package, Signal processing

June 9, 2012 by hgpu

Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines

Jonathan Ragan-Kelley, Andrew Adams, Sylvain Paris, Marc Levoy, Saman Amarasinghe, Fredo Durand

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Tags: Algorithms, CUDA, Filtering, Image processing, nVidia, Tesla C2070

June 8, 2012 by hgpu

Generating Device-specific GPU code for Local Operators in Medical Imaging

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

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Code generation, CUDA, Image processing, Medicine, nVidia, nVidia Quadro FX 5800, OpenCL, RapidMind, Tesla C2050

June 1, 2012 by hgpu

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Matthew Sellitto

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Tags: Algorithms, Heterogeneous systems, Image processing, nVidia, OpenCL, Optimization, Sensing, Tesla M2070, Thesis

May 30, 2012 by hgpu

Performance-Analysis-Based Acceleration of Image Quality Assessment

Thien Phan, Sohum Sohoni, Damon M. Chandler, Eric C. Larson

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

May 29, 2012 by hgpu

CUDA Implementation of Parallel Algorithms for Animal Noseprint Identification

Vincent Stanley Dayes

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Tags: Algorithms, CUDA, Image processing, Image registration, nVidia, nVidia GeForce 8400 GS, Thesis

May 29, 2012 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

Two Stage Data Mining Technique for Fast Monsoon Onset Prediction

API-Compiling for Image Hardware Accelerators

CUDA-accelerated Hierarchical K-means

A Parallel Image Segmentation Algorithm on GPUs

GPU Computing: Image Convolution

Point to point processing of digital images using parallel computing

Fast Morphological Image Processing Open-Source Extensions for GPU processing with CUDA

Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines

Generating Device-specific GPU code for Local Operators in Medical Imaging

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Performance-Analysis-Based Acceleration of Image Quality Assessment

CUDA Implementation of Parallel Algorithms for Animal Noseprint Identification

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)