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GPU accelerated pathfinding

Avi Bleiweiss

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Presentation, Search strategies

October 27, 2010 by hgpu

Fast parallel GPU-sorting using a hybrid algorithm

E. Sintorn, U. Assarsson

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Tags: Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce 8800 GTX, Sorting

October 27, 2010 by hgpu

GPU acceleration of a production molecular docking code

Bharat Sukhwani, Martin C. Herbordt

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Tags: Bioinformatics, Biophysics, Chemistry, FPGA, Molecular dynamics, nVidia, Tesla C1060

October 27, 2010 by hgpu

GPU accelerated molecular dynamics simulation of thermal conductivities

Juekuan Yang, Yujuan Wang, Yunfei Chen

Tags: Computational Physics, Molecular dynamics, nVidia, Physics

October 27, 2010 by hgpu

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

M. J. Harvey, G. Giupponi, G. De Fabritiis

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Tags: Biological Physics, Chemistry, Computational Physics, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

GPU Cluster for High Performance Computing

Zhe Fan, Feng Qiu, A. Kaufman, S. Yoakum-Stover

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Tags: Computer science, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, nVidia GeForce FX 5800 Ultra

October 27, 2010 by hgpu

GPU Gems 3

Hubert Nguyen

Tags: Book, Computer science, nVidia, Programming techniques

October 27, 2010 by hgpu

Simulating spin models on GPU

Martin Weigel

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Source codes

Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Statistical Mechanics, Tesla C1060

October 27, 2010 by hgpu

Fast fluid dynamics simulation on the GPU

Mark Harris

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Source codes

Tags: Cg, Computer science, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, Package, Programming techniques

October 27, 2010 by hgpu

Getting Started with GPU Programming

Michael A. Gray

Tags: Computer science, Macintosh, nVidia, Tutorial

October 27, 2010 by hgpu

GPU implementation of JPEG XR

Ming C. Che, Jie Liang

Tags: Algorithms, Computer science, CUDA, Image processing, nVidia

October 27, 2010 by hgpu

Monte Carlo integration on GPU

J. Kanzaki

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Monte Carlo integration, nVidia, nVidia GeForce GTX 285, Package, Physics

October 27, 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

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high performance computing on graphics processing units: hgpu.org

GPU accelerated pathfinding

Fast parallel GPU-sorting using a hybrid algorithm

GPU acceleration of a production molecular docking code

GPU accelerated molecular dynamics simulation of thermal conductivities

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

GPU Cluster for High Performance Computing

GPU Gems 3

Simulating spin models on GPU

Fast fluid dynamics simulation on the GPU

Getting Started with GPU Programming

GPU implementation of JPEG XR

Monte Carlo integration on GPU

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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