high performance computing on graphics processing units: hgpu.org

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Phase Based Volume Registration on the GPU with Application to Quantitative MRI

Anders Eklund, Mats Andersson, Marcel Warntjes, Hans Knutsson

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Tags: CUDA, Image registration, Medicine, MRI, nVidia, nVidia GeForce GTX 285

March 5, 2011 by hgpu

Phase Based Volume Registration Using CUDA

Anders Eklund, Mats Andersson, Hans Knutsson

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Tags: CUDA, Image registration, Medicine, MRI, nVidia, Poster

March 5, 2011 by hgpu

How GPUs Can Improve the Quality of Magnetic Resonance Imaging

Sam S. Stone, Haoran Yi, Justin P. Haldar, Wen-mei W. Hwu, Bradley P. Sutton, and Zhi-Pei Liang

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Tags: CUDA, FFT, Image processing, Image reconstruction, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce 8800 GTX

February 20, 2011 by hgpu

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Grand Roman Joldes, Adam Wittek, Mathieu Couton, Simon K. Warfield and Karol Miller

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Tags: CUDA, Finite element method, Image processing, Image registration, Medicine, MRI, nVidia

February 5, 2011 by hgpu

Evaluating the Performance of Processing Medical Volume Data on Graphics Hardware

Matthias Raspe, Guido Lorenz and Stefan Muller

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Tags: Computed tomography, CT, Image processing, Medicine, MRI, nVidia, nVidia GeForce 8800 GTS

January 27, 2011 by hgpu

Sparse regularization in MRI iterative reconstruction using GPUs

Yue Zhuo, Bradley Sutton, Xiao-Long Wu, Justin Haldar, Wen-mei Hwu, Zhipei Liang

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Y. Zhuo, X-L. Wu, J. P. Haldar, W-M. W. Hwu, Z-P. Liang, and B. P. Sutton

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, Tesla S1070

January 24, 2011 by hgpu

Accelerating iterative field-compensated MR image reconstruction on GPUs

Yue Zhuo, Xiao-Long Wu, Justin P. Haldar, Wen-mei Hwu, Zhi-pei Liang, Bradley P. Sutton

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Tags: Conjugate gradient solver, CUDA, Image processing, Image reconstruction, Medicine, MRI, nVidia, nVidia GeForce GTX 280

January 24, 2011 by hgpu

Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware

David Levin, Usaf Aladl, Guido Germano, Piotr Slomka

Tags: ATI, ATI Radeon 9700 Pro, Computed tomography, CT, Image processing, Medicine, MRI, Rendering, Visualization

January 8, 2011 by hgpu

In vivo interactive visualization of four-dimensional blood flow patterns

Bernhard Kainz, Ursula Reiter, Gert Reiter, Dieter Schmalstieg

Tags: Image processing, Medicine, MRI, Visualization

December 15, 2010 by hgpu

Cartesian SENSE and k-t SENSE reconstruction using commodity graphics hardware

Michael S. Hansen, David Atkinson, Thomas S. Sorensen

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Tags: Image processing, Image reconstruction, Magnetic resonance imaging, Medicine, MRI

December 12, 2010 by hgpu

GPU-based Volume Rendering for Medical Image Visualization

Yang Heng, Lixu Gu

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Tags: Image processing, Medicine, MRI, nVidia, OpenGL, Rendering

November 29, 2010 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

Phase Based Volume Registration on the GPU with Application to Quantitative MRI

Phase Based Volume Registration Using CUDA

How GPUs Can Improve the Quality of Magnetic Resonance Imaging

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Evaluating the Performance of Processing Medical Volume Data on Graphics Hardware

Sparse regularization in MRI iterative reconstruction using GPUs

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Accelerating iterative field-compensated MR image reconstruction on GPUs

Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware

In vivo interactive visualization of four-dimensional blood flow patterns

Cartesian SENSE and k-t SENSE reconstruction using commodity graphics hardware

GPU-based Volume Rendering for Medical Image Visualization

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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