high performance computing on graphics processing units: hgpu.org

hgpu.org » Biomolecules

A GPU-accelerated Direct-sum Boundary Integral Poisson-Boltzmann Solver

Weihua Geng, Ferosh Jacob

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Tags: Biomolecules, CUDA, Electrostatics, Linear Algebra, Mathematics, Molecular surface, Numerical Analysis, nVidia, Poisson Boltzmann, Tesla M2070

January 25, 2013 by hgpu

GPU-Optimized Molecular Dynamics Simulations

Tyson J. Lipscomb

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Tags: Biology, Biomolecules, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Pseudo-random number generators, Review, RNA, Tesla C2070, Thesis

July 8, 2012 by hgpu

Multi-dimensional characterization of electrostatic surface potential computation on graphics processors

Mayank Daga, Wu-chun Feng

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Tags: Algorithms, Biology, Biomolecules, Computational Complexity, CUDA, Electrostatics, Molecular modeling, nVidia, Optimization, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

Timo Strunk, Moritz Wolf, Wolfgang Wenzel

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Biology, Biomolecules, Monte Carlo simulation, N-body simulation, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization

October 30, 2011 by hgpu

FPGA acceleration of rigid-molecule docking codes

Bharat Sukhwani, Martin C. Herbordt

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Tags: Biology, Biomolecules, CUDA, FPGA, Molecular modeling, nVidia, Performance, Tesla C1060

August 15, 2011 by hgpu

Molecular Dynamics Simulations Using Graphics Processing Units

John A. Baker, Jonathan D. Hirst

Tags: Biomolecules, Chemistry, Molecular dynamics, Molecular modeling

July 22, 2011 by hgpu

Massively parallelized replica-exchange simulations of polymers on GPUs

Jonathan Gross, Wolfhard Janke, Michael Bachmann

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Tags: Biomolecules, Computational Physics, Condensed matter, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Physics, Polymer Systems, Tesla C1060

July 19, 2011 by hgpu

Towards accelerating molecular modeling via multi-scale approximation on a GPU

M. Daga, Wu-chun Feng, T. Scogland

Tags: Algorithms, Biomolecules, Electrostatic potential, Medicine, Molecular modeling

May 5, 2011 by hgpu

Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

Fast Calculation of Electrostatic Potentials on the GPU or the ASIC MD-GRAPE-3

Tetsu Narumi, Kenji Yasuoka, Makoto Taiji, Francesco Zerbetto, Siegfried Hofinger

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Tags: Biomolecules, Biophysics, Chemistry, Molecular simulation, nVidia, nVidia GeForce GTX 280, Poisson Boltzmann

January 25, 2011 by hgpu

Langevin dynamics simulations of biomolecules on graphics processors

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

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Tags: Biological Physics, Biomolecules, Condensed matter, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 295, Physics, Soft Condensed Matter

November 12, 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

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

BoltzGen:Toward Universal Binder Design

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

A GPU-accelerated Direct-sum Boundary Integral Poisson-Boltzmann Solver

GPU-Optimized Molecular Dynamics Simulations

Multi-dimensional characterization of electrostatic surface potential computation on graphics processors

Development and evaluation of a GPU-optimized N-body term for the simulation of biomolecules

FPGA acceleration of rigid-molecule docking codes

Molecular Dynamics Simulations Using Graphics Processing Units

Massively parallelized replica-exchange simulations of polymers on GPUs

Towards accelerating molecular modeling via multi-scale approximation on a GPU

Probing biomolecular machines with graphics processors

Fast Calculation of Electrostatic Potentials on the GPU or the ASIC MD-GRAPE-3

Langevin dynamics simulations of biomolecules on graphics processors

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

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

BoltzGen:Toward Universal Binder Design

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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