high performance computing on graphics processing units: hgpu.org

hgpu.org » MRI

Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction

Michael Driscoll, Benjamin Brock, Frank Ong, Jonathan Tamir, Hsiou-Yuan Liu, Michael Lustig, Armando Fox, Katherine Yelick

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Tags: CUDA, FFT, Image processing, Image reconstruction, Intel Xeon Phi, Magnetic resonance imaging, Microscopy, MRI, nVidia, nVidia GeForce GTX Titan X, Package

June 13, 2018 by hgpu

Python Non-Uniform Fast Fourier Transform (PyNUFFT): An Accelerated Non-Cartesian MRI Package on a Heterogeneous Platform (CPU/GPU)

Jyh-Miin Lin

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Tags: Algorithms, CUDA, FFT, Heterogeneous systems, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 965 M, OpenCL, Package, Python, Tesla K80

March 31, 2018 by hgpu

Simulating the Cardinal Movements of Childbirth Using Finite Element Analysis on the Graphics Processing Unit

Zelimkhan Gerikhanov

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Tags: AMD Radeon HD 8970 M, ATI, Biology, Biomechanics, FEM, Finite element method, Medicine, MRI, OpenCL, Thesis

August 17, 2017 by hgpu

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Takuya Matsumoto, Kiminori Matsuzaki

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Tags: Computer science, CUDA, Haskell, Image processing, MRI, nVidia, nVidia GeForce GTX 750 Ti

April 3, 2017 by hgpu

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

Amir Alansary, Bernhard Kainz, Martin Rajchl, Maria Murgasova, Mellisa Damodaram, David F.A. Lloyd, Alice Davidson, Steven G. McDonagh, Mary Rutherford, Joseph V. Hajnal, Daniel Rueckert

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Tags: Computer science, CUDA, Magnetic resonance imaging, Motion compensation, MRI, nVidia, Package, Tesla K40

November 25, 2016 by hgpu

Optimizing Full Correlation Matrix Analysis of fMRI Data on Intel Xeon Phi Coprocessors

Yida Wang, Michael Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Ted Willke

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Tags: Algorithms, Computer science, Intel Xeon Phi, Magnetic resonance imaging, MRI, Performance

May 19, 2015 by hgpu

Medical imaging using CUDA

Thomas Kovac

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

October 25, 2014 by hgpu

High performance MRI simulations of motion on multi-GPU systems

Christos G Xanthis, Ioannis E Venetis, Anthony H Aletras

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Tags: CUDA, Magnetic resonance imaging, Medicine, MRI, nVidia, Physics, Tesla C2070, Tesla C2075

July 6, 2014 by hgpu

A Fast Mixed-Band Lifting Wavelet Transform on the GPU

Tran Minh Quan, Won-Ki Jeong

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Tags: Compression, CUDA, Discrete Wavelet Transform, Image processing, JPEG2000, MRI, nVidia, Sensing, Tesla M2090

June 20, 2014 by hgpu

GPU-Accelerated Dynamic Functional Connectivity Analysis for Functional MRI Data Using OpenCL

D. Akgün, Ü. Sakoğlu, M. Mete, J. Esquivel, B. Adinoff

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Tags: Biology, Magnetic resonance imaging, Medicine, MRI, Neuroscience, nVidia, nVidia GeForce GTX 660, OpenCL

June 9, 2014 by hgpu

Brain perfusion imaging: performance and accuracy

F. Zhu

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Tags: Computed tomography, CT, CUDA, Image processing, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce GTX 280, Thesis

June 7, 2014 by hgpu

3D data denoising via Non-Local means filter by using parallel GPU strategies

Salvatore Cuomo, Pasquale De Michele, Francesco Piccialli

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Tags: Algorithms, CUDA, Filtering, Image processing, Magnetic resonance imaging, MRI, nVidia, Tesla S2050

May 7, 2014 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction

Python Non-Uniform Fast Fourier Transform (PyNUFFT): An Accelerated Non-Cartesian MRI Package on a Heterogeneous Platform (CPU/GPU)

Simulating the Cardinal Movements of Childbirth Using Finite Element Analysis on the Graphics Processing Unit

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

Optimizing Full Correlation Matrix Analysis of fMRI Data on Intel Xeon Phi Coprocessors

Medical imaging using CUDA

High performance MRI simulations of motion on multi-GPU systems

A Fast Mixed-Band Lifting Wavelet Transform on the GPU

GPU-Accelerated Dynamic Functional Connectivity Analysis for Functional MRI Data Using OpenCL

Brain perfusion imaging: performance and accuracy

3D data denoising via Non-Local means filter by using parallel GPU strategies

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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