high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Chemistry

Development of a Flow Solver with Complex Kinetics on the Graphic Processing Units

Hai P. Le, Jean-Luc Cambier

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Tags: Chemistry, Computational Physics, CUDA, Finite volume method, Fluid dynamics, nVidia, Tesla C2050, Tesla C2070

October 25, 2011 by hgpu

Characterization of FPGA-based High Performance Computers

Karl Savio Pimenta Pereira

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Tags: Algorithms, Benchmarking, Chemistry, Computer science, CUDA, DSP, FFT, FPGA, Molecular dynamics, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Thesis

October 18, 2011 by hgpu

The Anatomy of High-Performance 2D Similarity Calculations

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Source codes

Tags: Algorithms, Biochemistry, Chemistry, Clustering, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

October 16, 2011 by hgpu

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

Benjamin G. Levine, John E. Stone, Axel Kohlmeyer

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Tags: Algorithms, Chemistry, CUDA, GPU cluster, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Visualization

September 21, 2011 by hgpu

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

John E. Stone, Jan Saam, David J. Hardy, Kirby L. Vandivort, Wen-mei W. Hwu, Klaus Schulten

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Tags: Algorithms, Chemistry, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, Programming techniques, Rendering, Visualization

September 7, 2011 by hgpu

Efficient Calculation of Pairwise Nonbonded Forces

Matt Chiu, Md. Ashfaquzzaman Khan, Martin C. Herbordt

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Tags: Chemistry, Electrostatics, FPGA, Molecular dynamics, Optimization, Performance

August 15, 2011 by hgpu

The distributed diagonal force decomposition method for parallelizing molecular dynamics simulations

Urban Borstnik, Benjamin T. Miller, Bernard R. Brooks, Dusanka Janezic

Tags: Algorithms, Chemistry, Computational chemistry, Molecular dynamics, Performance

August 8, 2011 by hgpu

Structural, dynamic, and electrostatic properties of fully hydrated DMPC bilayers from molecular dynamics simulations accelerated with graphical processing units (GPUs)

Narayan Ganesan, Brad A. Bauer, Timothy R. Lucas, Sandeep Patel, Michela Taufer

Tags: Algorithms, Chemistry, Computational chemistry, Electrostatic potential, Electrostatics, Molecular dynamics

August 8, 2011 by hgpu

GPU-accelerated atom and dynamic bond visualization using hyperballs: A unified algorithm for balls, sticks, and hyperboloids

Matthieu Chavent, Antoine Vanel, Alex Tek, Bruno Levy, Sophie Robert, Bruno Raffin, Marc Baaden

Tags: Algorithms, Chemistry, Macromolecule, Molecular modeling, Visualization

July 23, 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

Fat vs. Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

Guido Klingbeil, Radek Erban, Mike Giles, Philip K. Maini

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Tags: Chemistry, CUDA, nVidia, nVidia GeForce GTX 260, Programming techniques, Stochastic simulation

July 14, 2011 by hgpu

GPU Accelerated Chemical Similarity Calculation for Compound Library Comparison

Chao Ma, Lirong Wang, Xiang-Qun Xie

Tags: Algorithms, Chemistry, CUDA, Nearest neighbour, nVidia

July 6, 2011 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Development of a Flow Solver with Complex Kinetics on the Graphic Processing Units

Characterization of FPGA-based High Performance Computers

The Anatomy of High-Performance 2D Similarity Calculations

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

Efficient Calculation of Pairwise Nonbonded Forces

The distributed diagonal force decomposition method for parallelizing molecular dynamics simulations

Structural, dynamic, and electrostatic properties of fully hydrated DMPC bilayers from molecular dynamics simulations accelerated with graphical processing units (GPUs)

GPU-accelerated atom and dynamic bond visualization using hyperballs: A unified algorithm for balls, sticks, and hyperboloids

Molecular Dynamics Simulations Using Graphics Processing Units

Fat vs. Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

GPU Accelerated Chemical Similarity Calculation for Compound Library Comparison

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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