high performance computing on graphics processing units: hgpu.org

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Multi-GPU Implementation of a Hybrid Thermal Lattice Boltzmann Solver using the TheLMA Framework

C. Obrecht, F. Kuznik, Bernard Tourancheau, J.-J. Roux

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C1060

June 26, 2014 by hgpu

Computing on Knights and Kepler Architectures

G. Bortolotti, M. Caberletti, G. Crimi, A. Ferraro, F. Giacomini, M. Manzali, G. Maron, M. Pivanti, D. Salomoni, S. F. Schifano, R. Tripiccione, M. Zanella

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Tags: CUDA, Fluid dynamics, Intel Xeon Phi, Lattice Boltzmann model, nVidia, Tesla K20

June 18, 2014 by hgpu

A Portable OpenCL Lattice Boltzmann Code for Multi- and Many-core Processor Architectures

Enrico Calore, Sebastiano Fabio Schifano, Raffaele Tripiccione

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, Intel Xeon Phi, Lattice Boltzmann model, nVidia, OpenCL, Tesla K20

June 17, 2014 by hgpu

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, nVidia, OpenMPI, Tesla M2070

June 15, 2014 by hgpu

Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems

James E. McClure, Hao Wang, Jan F. Prins, Cass T. Miller, Wu-chun Feng

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Tags: Algorithms, CUDA, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, Tesla K20

May 23, 2014 by hgpu

targetDP: an Abstraction of Lattice Based Parallelism with Portable Performance

Alan Gray, Kevin Stratford

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Tags: CUDA, Data parallelism, Fluid dynamics, Intel Xeon Phi, Lattice Boltzmann model, nVidia, Tesla K40

May 20, 2014 by hgpu

Evolution of a double-front Rayleigh-Taylor system using a GPU-based high resolution thermal Lattice-Boltzmann model

P. Ripesi, L. Biferale, S.F. Schifano, R. Tripiccione

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C2050, Tesla K20

May 7, 2014 by hgpu

CUDA Implementation of a Lattice Boltzmann Method and Code Optimization

A. Jain

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C2075

March 22, 2014 by hgpu

Direct Numerical Simulation and Large Eddy Simulation on a Turbulent Wall-Bounded Flow Using Lattice Boltzmann Method and Multiple GPUs

Xian Wang, Yanqin Shangguan, Hiromichi KOBAYASHI, Takayuki AOKI, Naoyuki Onodera

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, Numerical simulation, nVidia, Tesla K20

February 16, 2014 by hgpu

Finite differences numerical method for two-dimensional superlattice Boltzmann transport equation and case comparison of CPU(C) and GPGPU(CUDA) implementations

Dmitri Priimak

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Tags: Algorithms, Computational Physics, CUDA, Finite difference, Lattice Boltzmann model, Materials Science, nVidia, nVidia GeForce GTX 680, Physics

January 25, 2014 by hgpu

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Luiz Otavio S. Ferreira, Lucas Monteiro Volpe

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 580, Visualization

January 19, 2014 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Source codes

Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Multi-GPU Implementation of a Hybrid Thermal Lattice Boltzmann Solver using the TheLMA Framework

Computing on Knights and Kepler Architectures

A Portable OpenCL Lattice Boltzmann Code for Multi- and Many-core Processor Architectures

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems

targetDP: an Abstraction of Lattice Based Parallelism with Portable Performance

Evolution of a double-front Rayleigh-Taylor system using a GPU-based high resolution thermal Lattice-Boltzmann model

CUDA Implementation of a Lattice Boltzmann Method and Code Optimization

Direct Numerical Simulation and Large Eddy Simulation on a Turbulent Wall-Bounded Flow Using Lattice Boltzmann Method and Multiple GPUs

Finite differences numerical method for two-dimensional superlattice Boltzmann transport equation and case comparison of CPU(C) and GPGPU(CUDA) implementations

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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