high performance computing on graphics processing units: hgpu.org

Zachary DeVito, Michael Mara, Michael Zollhofer, Gilbert Bernstein, Jonathan Ragan-Kelley, Christian Theobalt, Pat Hanrahan, Matthew Fisher, Matthias Niessner

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Tags: Comnputer science, Computer vision, CUDA, Image generation, Image processing, nVidia, Programming Languages

April 26, 2016 by hgpu

Fast LZW compression using a GPU

Shunji Funasaka, Koji Nakano, Yasuaki Ito

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, nVidia GeForce GTX 980

March 5, 2016 by hgpu

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

Matthew Marangoni, Thomas Wischgoll

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Tags: Code generation, Computer science, CUDA, Image processing, LLVM, nVidia, Tesla C1060

February 23, 2016 by hgpu

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Tobias Klein

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, Image processing, nVidia, nVidia Quadro 6000, OpenCL, Thesis, Visualization

January 29, 2016 by hgpu

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

Marco Cali, Valeria Di Mauro

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Tags: CUDA, Edge detection, Image processing, nVidia, nVidia GeForce GTX 845 M, OpenGL, Performance

January 16, 2016 by hgpu

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration

Christopher Robert Jackson

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Tags: Algorithms, Earth and Space Sciences, FPGA, Image processing, nVidia, nVidia GeForce GTX 690, OpenCL, Thesis

December 23, 2015 by hgpu

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

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

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

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

FPGA-Based Accelerator Design from a Domain-Specific Language

GPU-accelleration of image rendering and sorting algorithms with the OpenCL framework

Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

ImageCL: An Image Processing Language for Performance Portability on Heterogeneous Systems

Graphics Supercomputing Applied to Brain Image Analysis with NiftyReg

Parallel Wavelet Schemes for Images

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

Fast LZW compression using a GPU

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

Real time mitigation of atmospheric turbulence in long distance imaging using the lucky region fusion algorithm with FPGA and GPU hardware acceleration

Recent source codes

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

ROCm's implementation of Gromacs

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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