high performance computing on graphics processing units: hgpu.org

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GPU-based Iterative Cone Beam CT Reconstruction Using Tight Frame Regularization

Xun Jia, Bin Dong, Yifei Lou, Steve B. Jiang

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

November 10, 2010 by hgpu

Faster Radix Sort via Virtual Memory and Write-Combining

Jan Wassenberg, Peter Sanders

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Tags: Algorithms, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, Sorting

November 10, 2010 by hgpu

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

Christopher J. Fluke, David G. Barnes, Benjamin R. Barsdell, Amr H. Hassan

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Tags: Astrophysics, ATI, ATI Radeon HD 5970, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 8800 GT, OpenCL, Tesla C1060

November 10, 2010 by hgpu

GPU-based Low-dose 4DCT Reconstruction via Temporal Non-local Means

Zhen Tian, Xun Jia, Steve B. Jiang

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Tags: Computed tomography, CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060

November 10, 2010 by hgpu

Compressive Phase Contrast Tomography

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, C. Yang

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Tags: CUDA, FFT, nVidia, Optics, Physics, Radon transform, Tesla C1060, Tomography

November 10, 2010 by hgpu

Sop-GPU: Accelerating biomolecular simulations in the centisecond timescale using graphics processors

A. Zhmurov, R. I. Dima, Y. Kholodov, V. Barsegov

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Tags: Bioinformatics, Biomolecular assemblies, Chemistry, CUDA, Dynamic force spectroscopy, Langevin dynamics, Molecular dynamics, nVidia, nVidia GeForce GTX 295

November 9, 2010 by hgpu

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

How to obtain efficient GPU kernels: an illustration using FMM & FGT algorithms

Felipe A. Cruz, Simon K. Layton, Lorena A. Barba

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Tags: Computer science, CUDA, Fast summation methods, Mathematical Software, nVidia, Tesla C1060

November 9, 2010 by hgpu

General purpose Molecular Dynamics Simulations on GPUs: Issues of Pair Forces and Scaling to large Clusters

Christian Trott, Lars Winterfeld

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Source codes

Tags: Computational Physics, Condensed matter, CUDA, GPU cluster, Materials Science, Molecular dynamics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Performance, Physics, Tesla C1060, Tesla S1070

November 9, 2010 by hgpu

Improving many flavor QCD simulations using multiple GPUs

M. Hayakawa, K.-I. Ishikawa, Y. Osaki, S. Takeda, S. Uno, N. Yamada

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, OpenMP, Physics, QCD

November 9, 2010 by hgpu

Direct N-body simulations of globular clusters: (I) Palomar 14

Akram Hasani Zonoozi, Andreas H.W. Kuepper, Holger Baumgardt, Hosein Haghi, Pavel Kroupa, Michael Hilker

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Tags: Astrophysics, Galaxy Astrophysics, Globular clusters, GPU cluster, N-body simulation, nVidia, nVidia GeForce GTX 280

November 9, 2010 by hgpu

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarch, Yvonnick Le Menach, Jean-Luc Dekeyser

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla C870

November 9, 2010 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

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-based Iterative Cone Beam CT Reconstruction Using Tight Frame Regularization

Faster Radix Sort via Virtual Memory and Write-Combining

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

GPU-based Low-dose 4DCT Reconstruction via Temporal Non-local Means

Compressive Phase Contrast Tomography

Sop-GPU: Accelerating biomolecular simulations in the centisecond timescale using graphics processors

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

How to obtain efficient GPU kernels: an illustration using FMM & FGT algorithms

General purpose Molecular Dynamics Simulations on GPUs: Issues of Pair Forces and Scaling to large Clusters

Improving many flavor QCD simulations using multiple GPUs

Direct N-body simulations of globular clusters: (I) Palomar 14

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

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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