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

Michal Januszewski, Marcin Kostur

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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

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Juan Carlos Diaz Velez

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Tags: CUDA, High Energy Physics - Experiment, nVidia, Physics, Python, Tesla C1060, Tesla C2050, Tesla M2070, Thesis

October 24, 2013 by hgpu

A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers

Christopher D. Cooper, Jaydeep P. Bardhan, L. A. Barba

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Tags: Biomolecules, Boltzmann equation, Computational Physics, CUDA, Electrostatics, Intel Phi, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

September 17, 2013 by hgpu

Fast network communities visualization on massively parallel GPU architecture

M. Mrzek, B. Jerman Blazic

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Tags: Computer science, CUDA, nVidia, Python, Tesla M2090, Visualization

August 29, 2013 by hgpu

The development and expansion of HOOMD-blue through six years of GPU proliferation

Joshua A. Anderson, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 580, nVidia GeForce GTX Titan, Package, Physics, Python, Software Engineering, Tesla S1070

August 27, 2013 by hgpu

Estimating the WCET of GPU-Accelerated Applications using Hybrid Analysis

Adam Betts, Alastair Donaldson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, OpenCL, Package, Python, Tesla C2050

August 26, 2013 by hgpu

OpenCL programming using Python syntax

Massimo Di Pierro

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Tags: Computer science, OpenCL, Package, PyOpenCL, Python

August 26, 2013 by hgpu

AQUAgpusph, a free 3D SPH solver accelerated with OpenCL

J.L. Cercos-Pita, A. Souto-Iglesias, L.M. Gonzalez, F. Macia

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Tags: ATI, ATI Radeon HD 7970, Fluid dynamics, OpenCL, Python

August 3, 2013 by hgpu

The Astrophysical Multipurpose Software Environment

F.I. Pelupessy, A. van Elteren, N. de Vries, S.L.W. McMillan, N. Drost, S.F. Portegies Zwart

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, nVidia, Package, Python

July 21, 2013 by hgpu

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Matthias Alexander Lee

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Tags: Bioinformatics, Biology, Computational Complexity, CUDA, nVidia, Package, Python, RNA, Sequence alignment, Signal processing

May 31, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

See all packages

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high performance computing on graphics processing units: hgpu.org

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

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers

Fast network communities visualization on massively parallel GPU architecture

The development and expansion of HOOMD-blue through six years of GPU proliferation

Estimating the WCET of GPU-Accelerated Applications using Hybrid Analysis

OpenCL programming using Python syntax

AQUAgpusph, a free 3D SPH solver accelerated with OpenCL

The Astrophysical Multipurpose Software Environment

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Directive-based Approach to Heterogeneous Computing

Solving Wave Equations on Unstructured Geometries

Recent source codes

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

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