high performance computing on graphics processing units: hgpu.org

hgpu.org » Lattice Boltzmann model

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Alexander Strack, Marcel Graf, Alexander Van Craen, Dirk Pflüger

View

Download (PDF)

Source codes

Tags: AMD, AMD Radeon Instinct MI210, Computer science, Heterogeneous systems, Intel, Lattice Boltzmann model, nVidia, nVidia A30, Package, performance portability, SYCL, Visualization

August 4, 2026 by hgpu

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Andrea Montessori, Michele La Rocca, Giorgio Amati, Marco Lauricella, Adriano Tiribocchi, Sauro Succi

View

Download (PDF)

Source codes

Tags: cfd, CUDA, Fluid dynamics, HPC, Lattice Boltzmann model, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

February 4, 2024 by hgpu

Thread-safe lattice Boltzmann for high-performance computing on GPUs

Andrea Montessori, Marco Lauricella, Adriano Tiribocchi, Mihir Durve, Michele La Rocca, Giorgio Amati, Fabio Bonaccorso, Sauro Succi

View

Download (PDF)

Source codes

Tags: Algorithms, cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia A100, Package

April 23, 2023 by hgpu

Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI

Ao Xu, Bo-Tao Li

View

Download (PDF)

Tags: cfd, Fluid dynamics, Lattice Boltzmann model, MPI, OpenACC

November 13, 2022 by hgpu

Analytical Performance Estimation during Code Generation on Modern GPUs

Dominik Ernst, Markus Holzer, Georg Hager, Matthias Knorr, Gerhard Wellein

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, OpenCL, Package, Tesla A100, Tesla V100

May 8, 2022 by hgpu

Performance Comparison of Different OpenCL Implementations of LBM Simulation on Commodity Computer Hardware

Jelena Tekic, Predrag Tekic, Milos Rackovic

View

Download (PDF)

Tags: AMD Radeon R5 M420, AMD Radeon R5 M430, ATI, cfd, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 940, nVidia GeForce GTX 960, OpenCL, Performance, Tesla C2070

April 17, 2022 by hgpu

gLBM: A GPU enabled Lattice Boltzmann Method Library

Aaron Bray, Rachel B. Clipp, M. Umar Qureshi, Sorin Mitran, Andinet Enquobahrie

View

Download (PDF)

Source codes

Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Package

February 20, 2022 by hgpu

Accelerating LBM on a Tightly-Coupled Field Programmable Gate Array

Mateo Vázquez Maceiras

View

Download (PDF)

Tags: cfd, Fluid dynamics, FPGA, HLS, Lattice Boltzmann model, OpenCL, Thesis

October 17, 2021 by hgpu

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Tadeusz Tomczak

View

Download (PDF)

Source codes

Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX Titan XP, Package

September 5, 2021 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

Lettuce: PyTorch-based Lattice Boltzmann Framework

Mario Christopher Bedrunka, Dominik Wilde, Martin Kliemank, Dirk Reith, Holger Foysi, Andreas Krämer

View

Download (PDF)

Source codes

Tags: Algorithms, Computational Physics, CUDA, Deep learning, Fluid dynamics, Lattice Boltzmann model, Machine learning, nVidia, nVidia GeForce RTX 2070, Package, Physics, Tesla V100

June 27, 2021 by hgpu

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

Markus Holzer, Martin Bauer, Harald Kostler, Ulrich Rüde

View

Download (PDF)

Source codes

Tags: Algorithms, cfd, Code generation, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenCL, Package, Physics, Programming techniques, Tesla P100, Tesla V100

December 20, 2020 by hgpu

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Thread-safe lattice Boltzmann for high-performance computing on GPUs

Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI

Analytical Performance Estimation during Code Generation on Modern GPUs

Performance Comparison of Different OpenCL Implementations of LBM Simulation on Commodity Computer Hardware

gLBM: A GPU enabled Lattice Boltzmann Method Library

Accelerating LBM on a Tightly-Coupled Field Programmable Gate Array

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Lettuce: PyTorch-based Lattice Boltzmann Framework

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

Recent source codes

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Most viewed papers (last 30 days)