high performance computing on graphics processing units: hgpu.org

Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU

Wai-Man Pang, Jing Qin, Yuqiang Lu, Yongming Xie, Chee-Kong Chui, Pheng-Ann Heng

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Tags: Computed tomography, CT, CUDA, Image reconstruction, Medicine, Motion compensation, nVidia, nVidia GeForce 8800 GTX

November 17, 2010 by hgpu

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Xun Jia, Yifei Lou, John Lewis, Ruijiang Li, Xuejun Gu, Chunhua Men, William Y. Song, Steve B. Jiang

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

November 13, 2010 by hgpu

GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation

Xun Jia, Yifei Lou, Ruijiang Li, William Y. Song, Steve B. Jiang

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

November 12, 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

Real-time visualization of large volume datasets on standard PC hardware

Kai Xie, Jie Yang, Y. M. Zhu

Tags: Computed tomography, CT, Image processing, Medicine, nVidia, nVidia GeForce 6600

November 6, 2010 by hgpu

Graphics Hardware-Based Level-Set Method for Interactive Segmentation and Visualization

Helen Hong, Seongjin Park

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Tags: ATI, ATI Radeon 9600, Computed tomography, CT, DirectX, Image processing, Medicine, Rendering

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

Accelerating simultaneous algebraic reconstruction technique with motion compensation using CUDA-enabled GPU

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation

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

Real-time visualization of large volume datasets on standard PC hardware

Graphics Hardware-Based Level-Set Method for Interactive Segmentation and Visualization

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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