high performance computing on graphics processing units: hgpu.org

Gallagher Pryor, Brett Lucey, Sandeep Maddipatla, Chris McClanahan, John Melonakos, Vishwanath Venugopalakrishnan, Krunal Patel, Pavan Yalamanchili, James Malcolm

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Source codes

Tags: Computer science, CUDA, FFT, Image processing, Linear Algebra, nVidia, nVidia GeForce 9600, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package, PTX, Tesla C1060, Tesla C2070

September 26, 2011 by hgpu

Accelerating image recognition on mobile devices using GPGPU

Miguel Bordallo Lopez, Henri Nykanen, Jari Hannuksela, Olli Silven, Markku Vehvilainen

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Tags: Algorithms, Computer science, Image processing, Image recognition, OpenCL, OpenGL

September 25, 2011 by hgpu

OpenCL: a viable solution for high-performance medical image reconstruction?

Christian Siegl, H. G. Hofmann, B. Keck, M. Prummer, J. Hornegger

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Tags: ATI, ATI Radeon HD 5870, Image processing, Image reconstruction, nVidia, OpenCL, Optimization, Tesla C1060

September 24, 2011 by hgpu

Image super-resolution by vectorizing edges

Chia-Jung Hung, Chun-Kai Huang, Bing-Yu Chen

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Tags: Algorithms, Image processing

September 23, 2011 by hgpu

Analytical motion blur rasterization with compression

Carl Johan Gribel, Michael Doggett, Tomas Akenine-Moller

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Tags: Algorithms, Compression, Image processing, Performance, Rasterization

September 15, 2011 by hgpu

Translation-invariant two-dimensional discrete wavelet transform on graphics processing units

Dietmar Wippig, Bernd Klauer

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Tags: Algorithms, ATI, ATI Radeon HD 4870, Discrete Wavelet Transform, GLSL, Image processing, nVidia, nVidia GeForce GTX 280, OpenGL, Shaders

September 11, 2011 by hgpu

Challenges of medical image processing

Ingrid Scholl, Til Aach, Thomas M. Deserno, Torsten Kuhlen

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Tags: Algorithms, Data mining, Grid, Image processing, Medicine, Review, Virtual reality, Visualization

September 11, 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

Adaptable Two-Dimension Sliding Windows on NVIDIA GPUs with Runtime Compilation

Possible planet-forming regions on submillimetre images

Design space exploration towards a realtime and energy-aware GPGPU-based analysis of biosensor data

Generating GPU Code from a High-level Representation for Image Processing Kernels

High-level GPU computing with jacket for MATLAB and C/C++

Accelerating image recognition on mobile devices using GPGPU

OpenCL: a viable solution for high-performance medical image reconstruction?

Image super-resolution by vectorizing edges

Analytical motion blur rasterization with compression

Translation-invariant two-dimensional discrete wavelet transform on graphics processing units

Challenges of medical image 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

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