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GPU-based Low-dose 4DCT Reconstruction via Temporal Non-local Means

Zhen Tian, Xun Jia, Steve B. Jiang

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Tags: Computed tomography, CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060

November 10, 2010 by hgpu

GPU-based Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

Zhen Tian, Xun Jia, Kehong Yuan, Tinsu Pan, Steve B. Jiang

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Tags: Computed tomography, CT, CUBLAS, CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060

November 9, 2010 by hgpu

Parallel medical image reconstruction: from graphics processing units (GPU) to Grids

Maraike Schellmann, Sergei Gorlatch, Dominik Meilander, Thomas Kosters, Klaus Schafers, Frank Wubbeling, Martin Burger

Tags: Cell processor, CUDA, Image processing, Image reconstruction, Medicine, nVidia, PET, Tomography

November 8, 2010 by hgpu

High-performance cone beam reconstruction using CUDA compatible GPUs

Yusuke Okitsu, Fumihiko Ino, Kenichi Hagihara

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Tags: CUDA, Image processing, Image reconstruction, nVidia, nVidia GeForce 8800 GTX, Tesla C870

November 8, 2010 by hgpu

The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography

Bo Zhang, Xiang Yang, Fei Yang, Xin Yang, Chenghu Qin, Dong Han, Xibo Ma, Kai Liu, Jie Tian

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Tags: CUBLAS, CUDA, CULA, Image processing, Image reconstruction, Medicine, nVidia GeForce GT 240

November 8, 2010 by hgpu

Parallel GPU-based data-dependent triangulations

Michal Cervenansky, Zsolt Toth, Juraj Starinsky, Andrej Ferko, Milos Sramek

Tags: Image processing, Image reconstruction

November 6, 2010 by hgpu

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

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-based Low-dose 4DCT Reconstruction via Temporal Non-local Means

GPU-based Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

Parallel medical image reconstruction: from graphics processing units (GPU) to Grids

High-performance cone beam reconstruction using CUDA compatible GPUs

The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography

Parallel GPU-based data-dependent triangulations

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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