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hgpu.org » Programming » CUDA

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Vu Dinh Trung, Tran Van Lang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 250, Task scheduling

July 17, 2013 by hgpu

Early Experiences With The OpenMP Accelerator Model

Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan, Barbara Chapman

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Package, Tesla K20

July 17, 2013 by hgpu

Parallel heterogeneous Branch and Bound algorithms for multi-core and multi-GPU environments

Imen Chakroun

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Tags: Algorithms, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 17, 2013 by hgpu

Data Structures and Algorithms for Counting Problems on Graphs using GPU

Amlan Chatterjee, Sridhar Radhakrishnan, John K. Antonio

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, Tesla C1060, Tesla C2050, Tesla C2070

July 16, 2013 by hgpu

A New GPU-based Approach to the Shortest Path Problem

Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Path problems

July 16, 2013 by hgpu

Coupling Lattice Boltzmann Gas and Level Set Method for Simulating Free Surface Flow in GPU/CUDA Environment

Tomir Kryza, Witold Dzwinel

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 460

July 16, 2013 by hgpu

Object support for OpenMP-style programming of GPU clusters in Java

Carolin Wolf, Georg Dotzler, Ronald Veldema, Michael Philippsen

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Tags: Computer science, CUDA, GPU cluster, Java, nVidia, PC cluster, Tesla M1060

July 16, 2013 by hgpu

Efficient algorithms for the realistic simulation of fluids

Jesus Ojeda Contreras

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Tags: Algorithms, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce 9400 M, nVidia GeForce 9600 M GT, nVidia GeForce GTX 280, Thesis, Visualization

July 16, 2013 by hgpu

Hydrodynamic Computation with Hybrid Programming on CPU-GPU Clusters

Tingxing Dong, Veselin Dobrev, Tzanio Kolev, Robert Rieben, Stanimire Tomov, Jack Dongarra

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Tags: CUDA, FEM, Finite element method, Fluid dynamics, GPU cluster, Linear Algebra, MPI, nVidia, Tesla M2050, Tesla M2090

July 15, 2013 by hgpu

A framework for cost based optimization of hybrid CPU/GPU query plans in database systems

Sebastian Bress, Ingolf Geist, Eike Schallehn, Maik Mory, Gunter Saake

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia

July 15, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

Parallelization of SAT Algorithms on GPUs

Carlos Costa

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Tags: Algorithms, Computer science, CUDA, nVidia, SAT

July 15, 2013 by hgpu

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

An HPC Benchmark Survey and Taxonomy for Characterization

HDM: Home made Diffusion Models

Home-made Diffusion Model from Scratch to Hatch

General Matrix Multiplication (GEMM)

High Performance Matrix Multiplication

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Early Experiences With The OpenMP Accelerator Model

Parallel heterogeneous Branch and Bound algorithms for multi-core and multi-GPU environments

Data Structures and Algorithms for Counting Problems on Graphs using GPU

A New GPU-based Approach to the Shortest Path Problem

Coupling Lattice Boltzmann Gas and Level Set Method for Simulating Free Surface Flow in GPU/CUDA Environment

Object support for OpenMP-style programming of GPU clusters in Java

Efficient algorithms for the realistic simulation of fluids

Hydrodynamic Computation with Hybrid Programming on CPU-GPU Clusters

A framework for cost based optimization of hybrid CPU/GPU query plans in database systems

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Parallelization of SAT Algorithms on GPUs

Recent source codes

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

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