high performance computing on graphics processing units: hgpu.org

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Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing

Sergio Sanchez, German Leon, Antonio Plaza, Enrique S. Quintana-Orti

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Tags: ARM, CUDA, Energy-efficient computing, Image processing, nVidia, nVidia GeForce GTX 480, nVidia Quadro 1000 M, Tesla K20

May 5, 2014 by hgpu

Accelerating Ant Colony Optimization-based Edge Detection on the GPU using CUDA

Laurence Dawson, Iain A. Stewart

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, Metaheuristics, nVidia, nVidia GeForce GTX 580

April 30, 2014 by hgpu

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Kei Ikeda, Fumihiko Ino, Kenichi Hagihara

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Source codes

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

April 27, 2014 by hgpu

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

Sergio Orts-Escolano, Jose Garcia-Rodriguez, Vicente Morell, Miguel Cazorla, Jorge Azorin, Juan Manuel Garcia-Chamizo

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Tags: Computer science, Computer vision, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 480

April 24, 2014 by hgpu

Content Based Image Retrieval with Graphical Processing Unit

Bhavneet Kaur, Sonika Jindal

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Tags: Algorithms, CUDA, Image processing, Information Retrieval, nVidia

April 21, 2014 by hgpu

Rapid Rabbit: Highly Optimized GPU Accelerated Cone-Beam CT Reconstruction

Eric Papenhausen, Klaus Mueller

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Tags: Computed tomography, CT, CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 680

April 21, 2014 by hgpu

Feasibility Analysis of Bilateral Filtering by General Purpose Graphical Processing Unit Computing

Shruti S.Agrawal, C.K.Kurve

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Tags: Algorithms, CUDA, Filtering, Image processing, nVidia, Signal processing, Tesla K20

April 17, 2014 by hgpu

A First Order Primal-Dual Algorithm for Nonconvex TV^q Regularization

Thomas Mollenhoff, Evgeny Strekalovskiy, Daniel Cremers

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 680

April 14, 2014 by hgpu

MAP-based Brain Tissue Segmentation using Manifold Learning and Hierarchical Max-Flow regularization

Martin Rajchl, John S.H. Baxter, A. Jonathan McLeod, Jing Yuan, Wu Qiu, Terry M. Peters, James A. White, Ali R. Khan

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Tags: CUDA, Image processing, Medicine, nVidia, Self-organizing map, Tesla C2070

April 12, 2014 by hgpu

A New method to Design Accurate Images with Tree Structural Transformations

Neelima Gogineni, C Ganga Bhavani, V S Giridhar Akula

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Tags: Algorithms, CUDA, Image processing, Image recognition, nVidia

April 11, 2014 by hgpu

Parallel face Detection and Recognition on GPU

Shivashankar J. Bhutekar, Arati K. Manjaramkar

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 770

April 9, 2014 by hgpu

A New Digital Repository for Hyperspectral Imagery with Unmixing-Based Retrieval Functionality Implemented on GPUs

Jorge Sevilla, Antonio Plaza

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Tags: CUDA, Image processing, nVidia, Sensing, Tesla C2050

April 7, 2014 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

Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing

Accelerating Ant Colony Optimization-based Edge Detection on the GPU using CUDA

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

Content Based Image Retrieval with Graphical Processing Unit

Rapid Rabbit: Highly Optimized GPU Accelerated Cone-Beam CT Reconstruction

Feasibility Analysis of Bilateral Filtering by General Purpose Graphical Processing Unit Computing

A First Order Primal-Dual Algorithm for Nonconvex TV^q Regularization

MAP-based Brain Tissue Segmentation using Manifold Learning and Hierarchical Max-Flow regularization

A New method to Design Accurate Images with Tree Structural Transformations

Parallel face Detection and Recognition on GPU

A New Digital Repository for Hyperspectral Imagery with Unmixing-Based Retrieval Functionality Implemented on GPUs

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)