high performance computing on graphics processing units: hgpu.org

hgpu.org » Molecular dynamics

Multi-Level Ewald: A Hybrid Multigrid/Fast Fourier Transform Approach to the Electrostatic Particle-Mesh Problem

David S. Cerutti, David A. Case

Tags: Chemistry, Molecular dynamics, Molecular simulation

January 25, 2011 by hgpu

Implementing molecular dynamics on hybrid high performance computers – short range forces

W. Michael Brown, Peng Wang, Steven J. Plimpton, Arnold N. Tharrington

Tags: Chemistry, CUDA, GPU cluster, Molecular dynamics, nVidia, Physics

January 22, 2011 by hgpu

Gaussian split Ewald: A fast Ewald mesh method for molecular simulation

Yibing Shan, John L. Klepeis, Michael P. Eastwood, Ron O. Dror, David E. Shaw

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Tags: Algorithms, Chemistry, Molecular dynamics, Molecular modeling

January 20, 2011 by hgpu

Energy efficient biomolecular simulations with FPGA-based reconfigurable computing

Ananth Nallamuthu, Melissa C. Smith, Scott Hampton, Pratul K. Agarwal, Sadaf R. Alam

Tags: Bioinformatics, Biology, FPGA, Molecular dynamics

January 19, 2011 by hgpu

Towards microsecond biological molecular dynamics simulations on hybrid processors

Scott Hampton, Pratul K. Agarwal, Sadaf R. Alam, Paul S. Crozier

Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060, Tesla C2050

January 19, 2011 by hgpu

Optimal Utilization of Heterogeneous Resources for Biomolecular Simulations

Scott S. Hampton, Sadaf R. Alam, Paul S. Crozier, Pratul K. Agarwal

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Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060, Tesla C2050

January 19, 2011 by hgpu

Using generalized ensemble simulations and Markov state models to identify conformational states

Gregory R. Bowman, Xuhui Huang, Vijay S. Pande

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Source codes

Tags: CUDA, Molecular dynamics, Molecular modeling, nVidia, Package, Physics, Thermodynamics

January 16, 2011 by hgpu

Fast binding site mapping using GPUs and CUDA

Bharat Sukhwani, Martin C. Herbordt

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Tags: Bioinformatics, Biology, CUDA, Molecular dynamics, nVidia, Tesla C1060

January 11, 2011 by hgpu

Molecular Dynamics Simulations on Commodity GPUs with CUDA

Weiguo Liu, Bertil Schmidt, Gerrit Voss, Wolfgang Muller-Wittig

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Tags: Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce 8800 GTX

January 10, 2011 by hgpu

Towards Large-Scale Molecular Dynamics Simulations on Graphics Processors

Joseph E. Davis, Adnan Ozsoy, Sandeep Patel, Michela Taufer

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Tags: Biology, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia Quadro FX 5600

January 3, 2011 by hgpu

Analysis of a Computational Biology Simulation Technique on Emerging Processing Architectures

Jeremy S. Meredith, Sadaf R. Alam, Jeffrey S. Vetter

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Tags: Biology, Cell processor, Cg, Computational biology, Molecular dynamics, nVidia, nVidia GeForce 7900 GTX

January 2, 2011 by hgpu

A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

Nathan Schmid, Mathias Botschi, Wilfred F. Van Gunsteren

Tags: Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, nVidia Quadro FX 5800, Solvent effects

December 17, 2010 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Multi-Level Ewald: A Hybrid Multigrid/Fast Fourier Transform Approach to the Electrostatic Particle-Mesh Problem

Implementing molecular dynamics on hybrid high performance computers – short range forces

Gaussian split Ewald: A fast Ewald mesh method for molecular simulation

Energy efficient biomolecular simulations with FPGA-based reconfigurable computing

Towards microsecond biological molecular dynamics simulations on hybrid processors

Optimal Utilization of Heterogeneous Resources for Biomolecular Simulations

Using generalized ensemble simulations and Markov state models to identify conformational states

Fast binding site mapping using GPUs and CUDA

Molecular Dynamics Simulations on Commodity GPUs with CUDA

Towards Large-Scale Molecular Dynamics Simulations on Graphics Processors

Analysis of a Computational Biology Simulation Technique on Emerging Processing Architectures

A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

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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