Molecular dynamics | Page 7

hgpu.org » Molecular dynamics

The development and expansion of HOOMD-blue through six years of GPU proliferation

Joshua A. Anderson, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 580, nVidia GeForce GTX Titan, Package, Physics, Python, Software Engineering, Tesla S1070

August 27, 2013 by hgpu

Tight Binding Molecular Dynamics on CPU and GPU clusters

Dimitar Pashov

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Tags: Algorithms, CUDA, Electrostatics, Fortran, GPU cluster, Linear Algebra, Molecular dynamics, MPI, nVidia, Physics, Tesla K20

August 23, 2013 by hgpu

Implementing Molecular Dynamics on Hybrid High Performance Computers – Three-Body Potentials

W. Michael Brown, Masako Yamada

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Tags: Algorithms, Chemistry, CUDA, Molecular dynamics, nVidia, Package, Physics, Tesla K20

August 20, 2013 by hgpu

A GPU implementation for improved granular simulations with LAMMPS

Emmanuel N. Millan, Christian Ringl, Carlos S. Bederian, Maria Fabiana Piccoli, Carlos Garcia Garino, Herbert M. Urbassek, Eduardo M. Bringa

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Tags: CUDA, Molecular dynamics, nVidia, Performance, Physics, Tesla C2050, Tesla C2075, Tesla M2090

August 18, 2013 by hgpu

Molecular Dynamics Simulation of Multi-Scale Flows on GPUs

S. Mulla, S. Ivekovic, J.M. Reese

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Tags: Biology, Chemistry, CUDA, Molecular dynamics, nVidia, OpenCL, Tesla M2075

August 12, 2013 by hgpu

Hybrid Acceleration of a Molecular Dynamics Simulation Using Short-Ranged Potentials

Julian Hornich

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Tags: Algorithms, Chemistry, CUDA, Molecular dynamics, nVidia, Tesla M2090, Thesis

July 5, 2013 by hgpu

GPU-Optimized Hybrid Neighbor/Cell List Algorithm for Coarse-Grained Molecular Dynamics Simulations

Andrew J. Proctor

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Tags: Algorithms, Biomolecules, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Tesla C2070, Thesis

June 16, 2013 by hgpu

A flexible algorithm for calculating pair interactions on SIMD architectures

Szilard Pall, Berk Hess

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Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, nVidia, Physics

June 10, 2013 by hgpu

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Robin M. Betz, Ross C. Walker

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Tags: Benchmarking, Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, Software Engineering, Tesla M2090

May 21, 2013 by hgpu

Programming for scientific computing on peta-scale heterogeneous parallel systems

Yang Can-qun, Wu Qiang, Tang Tao, Wang Feng, Xue Jing-ling

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Tags: Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, Tesla M2050

May 13, 2013 by hgpu

GPU-SD and DPD Parallelization for Gromacs tools for molecular dynamics simulations

Nicolae Goga, Siewert Marrink, Ruxandra Cioromela, Florica Moldoveanu

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Tags: Algorithms, Bioinformatics, Biology, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9600 GT

April 21, 2013 by hgpu

Simulation of a flowing snow avalanche using molecular dynamics

Denizhan Gucer, Halil Bulent Ozguc

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Tags: Algorithms, Collision detection, Computer science, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GT, Rendering

March 14, 2013 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

The development and expansion of HOOMD-blue through six years of GPU proliferation

Tight Binding Molecular Dynamics on CPU and GPU clusters

Implementing Molecular Dynamics on Hybrid High Performance Computers – Three-Body Potentials

A GPU implementation for improved granular simulations with LAMMPS

Molecular Dynamics Simulation of Multi-Scale Flows on GPUs

Hybrid Acceleration of a Molecular Dynamics Simulation Using Short-Ranged Potentials

GPU-Optimized Hybrid Neighbor/Cell List Algorithm for Coarse-Grained Molecular Dynamics Simulations

A flexible algorithm for calculating pair interactions on SIMD architectures

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Programming for scientific computing on peta-scale heterogeneous parallel systems

GPU-SD and DPD Parallelization for Gromacs tools for molecular dynamics simulations

Simulation of a flowing snow avalanche using molecular dynamics

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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