high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Graphics Processing Unit Audio Signals Processing in Pure Data and PdCUDA an Implementation with the CUDA Runtime API

Charles Z. Henry

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Tags: Acoustics, CUDA, nVidia, Signal processing

May 1, 2012 by hgpu

Random Walks based Multi-Image Segmentation: Quasiconvexity Results and GPU-based Solutions

Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh

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Tags: Algorithms, CUDA, Image processing, Linear Algebra, nVidia, nVidia GeForce GTX 470, Optimization

April 28, 2012 by hgpu

The AGILE library for image reconstruction in biomedical sciences using graphics card hardware acceleration

Manuel Freiberger, Florian Knoll, Kristian Bredies, Hermann Scharfetter, Rudolf Stollberger

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Source codes

Tags: Algorithms, CUDA, Image processing, Image reconstruction, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 480, Package, Tomography

April 28, 2012 by hgpu

Radio Astronomy Beam Forming on Many-Core Architectures

Alessio Sclocco, Ana Lucia Varbanescu, Jan David Mol, Rob V. van Nieuwpoort

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Signal processing

April 25, 2012 by hgpu

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

Huayou Su, Mei Wen, Ju Ren, Nan Wu, Jun Chai, Chunyuan Zhang

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Tags: CUDA, DSP, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 260

April 23, 2012 by hgpu

Image Convolution Processing: a GPU versus FPGA Comparison

Lucas M. Russo, Emerson C. Pedrino, Edilson Kato, Valentin Obac Roda

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Tags: CUDA, FPGA, Image processing, nVidia, nVidia GeForce GTX 295, Performance

April 21, 2012 by hgpu

GPU computing in medical physics: A review

Guillem Pratx, Lei Xing

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Tags: CUDA, Image processing, Image reconstruction, Medical Physics, Medicine, nVidia, Review

April 19, 2012 by hgpu

Programming issues for video analysis on Graphics Processing Units

Juan Gomez Luna

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Signal processing, Thesis

April 12, 2012 by hgpu

Image Processing on Graphical Processing Units for faster DNA Sequencing

Joep Schreurs

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Tags: Algorithms, CUDA, Image processing, Image registration, nVidia, nVidia GeForce GTX 470

April 5, 2012 by hgpu

Depth Estimation using Open Compute Language (OpenCL)

Giovanni Visentini, Amit Gupta

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Tags: Algorithms, Computational Complexity, Image processing, nVidia, nVidia Quadro NVS 295, OpenCL

April 4, 2012 by hgpu

Performance evaluation of GPU memory hierarchy using the FFT

Jacobo Lobeiras, Margarita Amor, Ramon Doallo

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Tags: Benchmarking, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Performance, Signal processing

March 30, 2012 by hgpu

Massively Parallel Localization of Pulsed Signal Transitions Using a GPU

Vinitha Khambadkar, Lee Barford, Frederick C. Harris, Jr.

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Tags: Algorithms, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 480, Signal processing, Tesla C2050

March 26, 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

Graphics Processing Unit Audio Signals Processing in Pure Data and PdCUDA an Implementation with the CUDA Runtime API

Random Walks based Multi-Image Segmentation: Quasiconvexity Results and GPU-based Solutions

The AGILE library for image reconstruction in biomedical sciences using graphics card hardware acceleration

Radio Astronomy Beam Forming on Many-Core Architectures

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

Image Convolution Processing: a GPU versus FPGA Comparison

GPU computing in medical physics: A review

Programming issues for video analysis on Graphics Processing Units

Image Processing on Graphical Processing Units for faster DNA Sequencing

Depth Estimation using Open Compute Language (OpenCL)

Performance evaluation of GPU memory hierarchy using the FFT

Massively Parallel Localization of Pulsed Signal Transitions Using a GPU

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)