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PySPH: a Python-based framework for smoothed particle hydrodynamics

Prabhu Ramachandran, Kunal Puri, Aditya Bhosale, A Dinesh, Abhinav Muta, Pawan Negi, Rahul Govind, Suraj Sanka, Pankaj Pandey, Chandrashekhar Kaushik, Anshuman Kumar, Ananyo Sen, Rohan Kaushik, Mrinalgouda Patil, Deep Tavker, Dileep Menon, Vikas Kurapati, Amal S Sebastian, Arkopal Dutt, Arpit Agarwal

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Tags: cfd, Computational Physics, CUDA, Fluid dynamics, Mathematical Software, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

September 15, 2019 by hgpu

Efficient Interleaved Batch Matrix Solvers for CUDA

Andrew Gloster, Enda Carroll, Miguel Bustamante, Lennon O'Naraigh

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Tags: Algorithms, Computational Physics, Computer science, CUDA, Matrix inversion, nVidia, Package, Tesla V100

September 15, 2019 by hgpu

Efficient Simulation of Fluid Flow and Transport in Heterogeneous Media Using Graphics Processing Units (GPUs)

Hassan Dashtian, Muhammad Sahimi

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Tags: Computational Physics, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 880, Physics

August 18, 2019 by hgpu

Simple Iterative Incompressible Smoothed Particle Hydrodynamics

Abhinav Muta, Prabhu Ramachandran, Pawan Negi

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Tags: Benchmarking, Computational Physics, Fluid dynamics, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1070 Ti, OpenCL, Package, Poisson equation

August 11, 2019 by hgpu

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

Luc-Henri Jolly, Alejandro Duran, Louis Lagardere, Jay W. Ponder, Pengyu Ren, Jean-Philip Piquemal

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Tags: Chemical Physics, Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, Molecular dynamics, Molecular modeling, OpenMP, Package

June 5, 2019 by hgpu

cuSten – CUDA Finite Difference and Stencil Library

Andrew Gloster, Lennon O'Naraigh

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Tags: Computational Physics, Computer science, CUDA, Finite difference, MPI, nVidia, nVidia GeForce GTX Titan X, Package, PDEs

March 3, 2019 by hgpu

A Package for Multi-Dimensional Monte Carlo Integration on Multi-GPUs

Hong-zhong Wu, Junjie Zhang, Long-gang Pang, Qun Wang

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Tags: Computational Physics, Monte Carlo integration, nVidia, Package, Physics, Python, TensorFlow, Tesla K40

February 24, 2019 by hgpu

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung

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Tags: Chemical Physics, Code generation, Computational Physics, Factorization, nVidia, OpenCL, Package, Physics, Tesla C2075, Tesla K40

September 9, 2018 by hgpu

Cracks in the Sky: Abelian-Higgs Cosmic String Evolution with CUDA

J. R. C. C. C. Correia, C. J. A. P. Martins

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia Quadro P 5000, Physics

September 9, 2018 by hgpu

cuPentBatch – A batched pentadiagonal solver for NVIDIA GPUs

Andrew Gloster, Lennon O Naraigh, Khang Ee Pang

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Tags: Computational Physics, CUDA, Differential equations, nVidia, nVidia GeForce GTX Titan X, Package, Partial differential equations, PDEs, Physics

July 21, 2018 by hgpu

Strategies for the Heterogeneous Execution of Large-Scale Simulations on Hybrid Supercomputers

Xavier Alvarez, Andrey Gorobets, F. Xavier Trias

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Tags: cfd, Computational Physics, Fluid dynamics, Heterogeneous systems, HPC, Hybrid computing, MPI, nVidia, OpenCL, Sparse matrix, Tesla K40

June 24, 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

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Masivo: Parallel public transport routes simulation

Masivo: Parallel Simulation Model Based on OpenCL for Massive Public Transportation Systems’ Routes

FBLAS: BLAS implementation for Intel FPGA

FBLAS: Streaming Linear Algebra Kernels on FPGA

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

Titan: A CUDA-based physics simulation sandbox for high-performance robotics, physics, and reinforcement learning applications

Titan: A Parallel Asynchronous Library for Multi-Agent and Soft-Body Robotics using NVIDIA CUDA

onYourMarks: A deep learning benchmark implementation for Nvidia's Jetson TX2

Benchmarking Deep Learning Models on Jetson TX2

Hacking Neural Networks: A small course on exploiting and defending neural networks

Hacking Neural Networks: A Short Introduction

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

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Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

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13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

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Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

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26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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high performance computing on graphics processing units: hgpu.org

PySPH: a Python-based framework for smoothed particle hydrodynamics

Efficient Interleaved Batch Matrix Solvers for CUDA

Efficient Simulation of Fluid Flow and Transport in Heterogeneous Media Using Graphics Processing Units (GPUs)

Simple Iterative Incompressible Smoothed Particle Hydrodynamics

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

cuSten – CUDA Finite Difference and Stencil Library

A Package for Multi-Dimensional Monte Carlo Integration on Multi-GPUs

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Cracks in the Sky: Abelian-Higgs Cosmic String Evolution with CUDA

cuPentBatch – A batched pentadiagonal solver for NVIDIA GPUs

Strategies for the Heterogeneous Execution of Large-Scale Simulations on Hybrid Supercomputers

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Recent source codes

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Masivo: Parallel public transport routes simulation

FBLAS: BLAS implementation for Intel FPGA

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

Titan: A CUDA-based physics simulation sandbox for high-performance robotics, physics, and reinforcement learning applications

onYourMarks: A deep learning benchmark implementation for Nvidia's Jetson TX2

Hacking Neural Networks: A small course on exploiting and defending neural networks

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

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Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019