high performance computing on graphics processing units: hgpu.org

Applications

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo Perez-Lemus, Riccardo Alessandri, Siva Dasetty, Cintia A. Menéndez, Yiheng Wu, Yezhi Jin, Trung Nguyen, John Parker, Andrew L. Ferguson, Juan J. de Pablo

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Tags: Biology, Chemistry, Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Python, Tesla V100

January 22, 2023 by hgpu

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics

Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis

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Tags: Biology, Chemistry, CUDA, GeForce RTX 2080 Ti, Machine learning, Molecular dynamics, Molecular simulation, Neural networks, nVidia, Package

January 23, 2022 by hgpu

Accelerating AutoDock VINA with GPUs

Shidi Tang, Ruiqi Chen, Mengru Lin, Qingde Lin, Yanxiang Zhu, Jiansheng Wu, Haifeng Hu, Ming Ling

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Tags: Chemistry, Databases, Heterogeneous systems, molecular docking, nVidia, nVidia GeForce GTX 1060, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, OpenCL, Package

October 17, 2021 by hgpu

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search

Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, and Stefano Forli

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Tags: Algorithms, Chemistry, Macromolecule, molecular docking, OpenCL, Package, Physics

February 28, 2021 by hgpu

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Szilárd Páll, Artem Zhmurov, Paul Bauer, Mark Abraham, Magnus Lundborg, Alan Gray, Berk Hess, Erik Lindahl

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Tags: Algorithms, AMD Radeon Instinct Mi50, AMD Vega FE, ATI, Chemistry, CUDA, Heterogeneous systems, Molecular dynamics, MPI, nVidia, nVidia GeForce RTX 2080, nVidia Quadro P 6000, OpenCL, Package, Tesla V100

June 21, 2020 by hgpu

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

Leonardo Solis-Vasquez, Diogo Santos-Martins, Andreas Koch, Stefano Forli

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Tags: AMD Radeon RX Vega 56, ATI, Biology, Chemistry, Energy-efficient computing, Heterogeneous systems, molecular docking, nVidia, OpenCL, Tesla V100

March 1, 2020 by hgpu

JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

Samuel S. Schoenholz, Ekin D. Cubuk

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Tags: Biochemistry, Chemistry, Computational Physics, CUDA, Fortran, Machine learning, Materials Science, Molecular dynamics, Neural networks, nVidia, Package, Physics, Python

December 15, 2019 by hgpu

libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications

Jocelyn Sunseri, David Ryan Koes

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Tags: Chemistry, Computer science, CUDA, Deep learning, Machine learning, Molecular modeling, Neural networks, nVidia, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan X, Package, PyTorch, TensorFlow

December 15, 2019 by hgpu

Code Optimization on GPUs

Changwan Hong

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Tags: Chemistry, Code generation, Computational chemistry, Computer science, CUDA, Intel Xeon Phi, Matrix multiplication, nVidia, Optimization, Sparse matrix, Tesla P100, Thesis

November 3, 2019 by hgpu

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

Ada Sedova, Andreas Tillack, Arnold Tharrington

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Tags: Chemistry, Molecular dynamics, Molecular simulation, nVidia, OpenACC, performance portability, Physics, Tesla K20

March 3, 2019 by hgpu

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

Leonardo Solis-Vasquez, Andreas Koch

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Tags: Chemistry, FPGA, Molecular dynamics, OpenCL, Package

August 11, 2018 by hgpu

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Moritz Kreutzer, Georg Hager, Dominik Ernst, Holger Fehske, Alan R. Bishop, Gerhard Wellein

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Tags: Chemistry, Computational Physics, Computer science, CUDA, Intel Xeon Phi, nVidia, OpenMP, Package, Performance, Physics, Quantum Physics, Tesla P100

March 10, 2018 by hgpu

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FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

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high performance computing on graphics processing units: hgpu.org

Applications

PySAGES: flexible, advanced sampling methods accelerated with GPUs

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics

Accelerating AutoDock VINA with GPUs

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications

Code Optimization on GPUs

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Recent source codes

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

Shine compiler for the RISE language

Cramming the training of a (BERT-type) language model into limited compute

oneDNN: oneAPI Deep Neural Network Library

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