high performance computing on graphics processing units: hgpu.org

Applications

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Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs

Mark Mawson, Alistair Revell

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia Quadro K5000, Performance, Review, Tesla K20

September 11, 2013 by hgpu

Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

Christopher D. Marcotte, Roman O. Grigoriev

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Tags: Chaotic Dynamics, Computational Physics, Nonlinear Sciences, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Physics

September 9, 2013 by hgpu

A GPU Implementation for Two-Dimensional Shallow Water Modeling

Kerry A. Seitz Jr., Alex Kennedy, Owen Ransom, Bassam A. Younis, John D. Owens

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 680

September 9, 2013 by hgpu

GPU Accelerated Particle Visualization with Splotch

Marzia Rivi, Claudio Gheller, Mel Krokos, Klaus Dolag, Martin Reinecke

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Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, MPI, Numerical simulation, nVidia, Rendering, Tesla M2090, Visualization

September 9, 2013 by hgpu

Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs

Furong Huang, Niranjan U N, Mohammad Umar Hakeem, Prateek Verma, Animashree Anandkumar

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Tags: Computer science, CUDA, CULA, Machine learning, nVidia, nVidia Quadro K4000, nVidia Quadro K5000

September 9, 2013 by hgpu

Acceleration of iterative Navier-Stokes solvers on graphics processing units

Tomczak, T., Zadarnowska, K., Koza, Z., Matyka, M., Miroslaw, L.

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Tags: CUDA, Finite volume method, Fluid dynamics, GPU, hardware acceleration, incompressible flow, Navier-Stokes solvers, OpenFOAM, operator splitting, Parallelization, PISO, SIMPLE

September 9, 2013 by Vratis

Combining recent HPC techniques for 3D geophysics acceleration

L. Boillot, E. Agullo, G. Bosilca, H. Calandra

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Tags: Geoscience, Intel Xeon Phi, Seismic modeling

September 7, 2013 by hgpu

Percolation study of samples on 2D lattices using GPUs

D.A. Matoz-Fernandez, P.M. Pasinetti, A.J. Ramirez-Pastor

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Tags: CUDA, Materials Science, Mathematics, nVidia, nVidia GeForce GTX 480, Physics

September 6, 2013 by hgpu

Efficient Implementation of RLS-Based Adaptive Filters on nVIDIA GeForce Graphics Processing Unit

A. Hirano, K. Nakayama

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Tags: CUDA, Filtering, nVidia, nVidia GeForce 8800 GTS, Signal processing

September 5, 2013 by hgpu

Real-Time Motion Artifact Compensation for PMD-ToF Images

T. Hoegg, D. Lefloch, A. Kolb

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Tags: CUDA, Image processing, Motion compensation, nVidia, nVidia GeForce GTX 680

September 5, 2013 by hgpu

Work in Progress: Vortex Detection and Visualization for Design of Micro Air Vehicles and Turbomachinery

R.J. Vickery, H. Thornburg, T. Wischgoll, C. Koehler, H. Dong, M. Pickett, N. Eikenberry, L. Harris, R. Snyder, D. Sanders, R. Hand

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia

September 5, 2013 by hgpu

GPU & CPU implementation of Young – Van Vliet’s Recursive Gaussian Smoothing Filter

I. Vidal-Migallón, O. Commowick, X. Pennec, J. Dauguet, T Vercauteren

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Tags: ATI Radeon HD 6970, CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 650, OpenCL

September 5, 2013 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

Memory transfer optimization for a lattice Boltzmann solver on Kepler architecture nVidia GPUs

Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

A GPU Implementation for Two-Dimensional Shallow Water Modeling

GPU Accelerated Particle Visualization with Splotch

Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs

Acceleration of iterative Navier-Stokes solvers on graphics processing units

Combining recent HPC techniques for 3D geophysics acceleration

Percolation study of samples on 2D lattices using GPUs

Efficient Implementation of RLS-Based Adaptive Filters on nVIDIA GeForce Graphics Processing Unit

Real-Time Motion Artifact Compensation for PMD-ToF Images

Work in Progress: Vortex Detection and Visualization for Design of Micro Air Vehicles and Turbomachinery

GPU & CPU implementation of Young – Van Vliet’s Recursive Gaussian Smoothing Filter

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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