high performance computing on graphics processing units: hgpu.org

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Building Human Brain Network in 3D Coefficient Map Determined by X-ray Microtomography

Ryuta Mizutani, Akihisa Takeuchi, Kentaro Uesugi, Susumu Takekoshi, Naoya Nakamura, Yoshio Suzuki

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Tags: Biology, CUDA, Image reconstruction, Medicine, nVidia, nVidia GeForce GTX 470, Package, Tomography

December 30, 2011 by hgpu

EM+TV for Reconstruction of Cone-beam CT with Curved Detectors using GPU

Jianwen Chen, Ming Yan, Luminita A. Vese, John Villasenor, Alex Bui, Jason Cong

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Tags: Algorithms, Computed tomography, CT, CUDA, Image reconstruction, Medicine, nVidia, Tesla C1060, Tomography

December 3, 2011 by hgpu

CT image reconstruction with half precision floating-point values

Clemens Maass, Sven Steckmann, Matthias Baer, Lars Hillebrand, Willi A. Kalender, Marc Kachelriess

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Tags: Algorithms, Computed tomography, CT, CUDA, Image processing, Image reconstruction, Larrabee, Medicine, nVidia, nVidia GeForce GTX 280

November 21, 2011 by hgpu

High-performance Blob-based iterative reconstruction of electron tomography on multi-GPUs

Xiaohua Wan, Fa Zhang, Qi Chu, Zhiyong Liu

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Tags: Biology, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX 295, OpenMP, Tomography

November 15, 2011 by hgpu

Advanced MRI reconstruction toolbox with accelerating on GPU

Xiao-Long Wu, Yue Zhuo, Fan Lam, Maojing Fu, Justin P. Haldar, Wen-Mei Hwu, Zhi-Pei Liang, Bradley P. Sutton, Jiading Gai

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Tags: Algorithms, CUDA, FFT, Image reconstruction, Magnetic resonance imaging, MRI, nVidia, nVidia GeForce GTX 280, Optimization, Physics

November 6, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Self-calibration of geometric and radiometric parameters for cone-beam computed tomography

Wolfgang Wein, Alexander Ladikos and Armin Baumgartner

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computed tomography, CT, Image reconstruction, Medicine, nVidia, nVidia GeForce GTX 580, Tomography

October 27, 2011 by hgpu

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

W.J. Palenstijna, K.J. Batenburga, J. Sijbersa

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Tags: Biology, Image reconstruction, Medicine, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Tomography

October 8, 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

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

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

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Tags: Algorithms, Cell processor, Grid, Image reconstruction, Medicine, PET, PET scanning, Tomography

September 16, 2011 by hgpu

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

Florian Stock, Andreas Koch

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Tags: Cell processor, Conjugate gradient solver, CUDA, FPGA, Image processing, Image reconstruction, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, Optimization, Sparse matrix

September 8, 2011 by hgpu

A GPU Accelerated Algorithm for Compressive Sensing Based Image Super-Resolution

Xifei Wu, Hui Xiang, Peng Lu

Tags: Algorithms, ATI, ATI Stream, Compression, Computer science, Image reconstruction

September 2, 2011 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Building Human Brain Network in 3D Coefficient Map Determined by X-ray Microtomography

EM+TV for Reconstruction of Cone-beam CT with Curved Detectors using GPU

CT image reconstruction with half precision floating-point values

High-performance Blob-based iterative reconstruction of electron tomography on multi-GPUs

Advanced MRI reconstruction toolbox with accelerating on GPU

Matrix inversion speed up with CUDA

Self-calibration of geometric and radiometric parameters for cone-beam computed tomography

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

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

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

A GPU Accelerated Algorithm for Compressive Sensing Based Image Super-Resolution

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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