high performance computing on graphics processing units: hgpu.org

Siavash Khallaghi, Purang Abolmaesumi, Ren Hui Gong, Elvis Chen, Sean Gill, Jonathan Boisvert, David Pichora, Dan Borschneck, Gabor Fichtinger, Parvin Mousavi

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Tags: CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 285, Optimization, Ultrasound

January 18, 2012 by hgpu

Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images

Fabian Lecron, Sidi Ahmed Mahmoudi, Mohammed Benjelloun, Said Mahmoudi, Pierre Manneback

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Tags: CUDA, Heterogeneous systems, Image processing, Medicine, nVidia, Tesla C1060

January 18, 2012 by hgpu

An Adaptive Step Size GPU ODE Solver for Simulating the Electric Cardiac Activity

Victor M. Garcia, A. Liberos, A.M. Climent, A. Vidal, J. Millet, A. Gonzalez

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Tags: CUDA, Differential equations, Heart, Medicine, nVidia, ODEs, Ordinary differential equations

January 17, 2012 by hgpu

Four-dimensional Cone Beam CT Reconstruction and Enhancement using a Temporal Non-Local Means Method

Xun Jia, Zhen Tian, Yifei Lou, Jan-Jakob Sonke, Steve B. Jiang

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Tags: Algorithms, Computed tomography, CT, CUDA, Medical Physics, Medicine, nVidia, Physics, Tesla C1060, Tomography

January 17, 2012 by hgpu

Efficient Convex Optimization Approaches to Variational Image Fusion

Jing Yuan, Brandon Miles, Juan Shi, Greg Garvin, Xue-Cheng Tai, Aaron Fenster

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Tags: Algorithms, CUDA, Image processing, Medicine, nVidia, Optimization, Sensing, Tesla C1060

January 13, 2012 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

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high performance computing on graphics processing units: hgpu.org

Applications

Joint-MAP Tomographic Reconstruction with Patch Similarity Based Mixture Prior Model

Multiscale Hemodynamics Using GPU Clusters

FPGA accelerated 3D reconstruction using compressive sensing

Graphical processing unit implementation of an integrated shape-based active contour: Application to digital pathology

Fast CT Image Processing using Parallelized Non-local Means

Accounting for Uncertainty in Medical Data: A CUDA Implementation of Normalized Convolution

Efficient fMRI Analysis and Clustering on GPUs

GPU Accelerated Registration of a Statistical Shape Model of the Lumbar Spine to 3D Ultrasound Images

Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images

An Adaptive Step Size GPU ODE Solver for Simulating the Electric Cardiac Activity

Four-dimensional Cone Beam CT Reconstruction and Enhancement using a Temporal Non-Local Means Method

Efficient Convex Optimization Approaches to Variational Image Fusion

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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