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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

The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography

Bo Zhang, Xiang Yang, Fei Yang, Xin Yang, Chenghu Qin, Dong Han, Xibo Ma, Kai Liu, Jie Tian

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Tags: CUBLAS, CUDA, CULA, Image processing, Image reconstruction, Medicine, nVidia GeForce GT 240

November 8, 2010 by hgpu

Accelerating Resolution-of-the-Identity Second-Order Moller-Plesset Quantum Chemistry Calculations with Graphical Processing Units

Leslie Vogt, Roberto Olivares-Amaya, Sean Kermes, Yihan Shao, Carlos Amador-Bedolla, Alan Aspuru-Guzik

Tags: Chemistry, Computational chemistry, CUBLAS, CUDA, Molecular modeling, nVidia, nVidia Quadro FX 5600

November 2, 2010 by hgpu

Graphics Processing Units and High-Dimensional Optimization

Hua Zhou, Kenneth Lange, Marc A. Suchard

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Tags: Block relaxation, CUBLAS, CUDA, EM and MM algorithms, Mathematics, Multidimensional scaling, Nonnegative matrix factorization, nVidia, nVidia GeForce GTX 280, PET scanning, Statistics

October 30, 2010 by hgpu

Accelerating Image Retrieval Using Factorial Correspondence Analysis on GPU

Nguyen-Khang Pham, Annie Morin, Patrick Gros

Tags: CUBLAS, CUDA, Factorial correspondence analysis, Image processing, nVidia, SIFT

October 29, 2010 by hgpu

The gputools package enables GPU computing in R

Joshua Buckner, Justin Wilson, Mark Seligman, Brian Athey, Stanley Watson, Fan Meng

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Source codes

Tags: Computer science, CUBLAS, CUDA, nVidia, Package

October 28, 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

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high performance computing on graphics processing units: hgpu.org

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

The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography

Accelerating Resolution-of-the-Identity Second-Order Moller-Plesset Quantum Chemistry Calculations with Graphical Processing Units

Graphics Processing Units and High-Dimensional Optimization

Accelerating Image Retrieval Using Factorial Correspondence Analysis on GPU

The gputools package enables GPU computing in R

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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