high performance computing on graphics processing units: hgpu.org

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Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Xiong QinGang, Li Bo, Xu Ji, Fang XiaoJian, Wang XiaoWei, Wang LiMin, He XianFeng, Ge Wei

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Tags: Algorithms, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Numerical simulation, nVidia, Tesla C2050

February 22, 2012 by hgpu

The Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

January 31, 2012 by hgpu

Numerical Ocean Modeling and Simulation with CUDA

Jason Mak, Paul Choboter, Chris Lupo

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Tags: Computer science, CUDA, Earth and Space Sciences, Finite difference, Fortran, MPI, nVidia, nVidia GeForce GTX 470

January 30, 2012 by hgpu

Parallel FEM Simulation Using GPUs

Vishnukanthan Kandasamy

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Tags: Computer science, CUDA, FEM, Finite element method, MPI, nVidia

January 21, 2012 by hgpu

Automated Techniques for Enabling Efficient MPI Application Migration

Karolina Sarnowska-Upton, Andrew Grimshaw

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Tags: Computer science, MPI, Programming techniques

January 20, 2012 by hgpu

Combining approximate inference methods for efficient learning on large computer clusters

Zhenwen Dai, Jacquelyn A. Shelton, Jorg Bornschein, Abdul Saboor Sheikh, Jorg Lucke

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Tags: Algorithms, Computational Complexity, Computer science, GPU cluster, Machine learning, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Python

January 19, 2012 by hgpu

Investigation of Parallel Computation – MPI, CUDA and Parallel Visualization

Lei Fan

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Tags: Algorithms, Computer science, CUDA, Fluid dynamics, MPI, nVidia, OpenGL, Sorting, Visualization

January 18, 2012 by hgpu

CPU/GPU computing for long-wave radiation physics on large GPU clusters

Fengshun Lu, Junqiang Song, Xiaoqun Cao, Xiaoqian Zhu

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Tags: CUDA, Earth and Space Sciences, Geoscience, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenMP, Tesla M2050

January 17, 2012 by hgpu

Programming on Parallel Machines: GPU, Multicore, Clusters and More

Norm Matloff

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Tags: Book, Computer science, CUDA, MPI, nVidia, Package, Programming techniques, Review, Tutorial

January 16, 2012 by hgpu

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Yifeng Chen, Xiang Cui, Hong Mei

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Tags: Code generation, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, MPI, nVidia, Optimization, Performance, Programming techniques, Pthreads, Tesla C1060

January 5, 2012 by hgpu

A Parallel Supercomputer Implementation of a Biological Inspired Neural Network and its use for Pattern Recognition

Vincent de Ladurantaye, Jean Lavoie, Jocelyn Bergeron, Maxime Parenteau, Huizhong Lu, Ramin Pichevar, Jean Rouat

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Tags: Biology, CUDA, MPI, Neural networks, nVidia, nVidia GeForce GTX 285, Pattern recognition

January 5, 2012 by hgpu

Decreasing NAME III Solution Time Using GP-GPU

Kingsley Gale-Sides

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Tags: Benchmarking, Cloud, Computer science, CUDA, Fortran, MPI, nVidia, Tesla C2050, Tesla M1060, Thesis

January 1, 2012 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

The Virtual OpenCL (VCL) Cluster Platform

Numerical Ocean Modeling and Simulation with CUDA

Parallel FEM Simulation Using GPUs

Automated Techniques for Enabling Efficient MPI Application Migration

Combining approximate inference methods for efficient learning on large computer clusters

Investigation of Parallel Computation – MPI, CUDA and Parallel Visualization

CPU/GPU computing for long-wave radiation physics on large GPU clusters

Programming on Parallel Machines: GPU, Multicore, Clusters and More

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

A Parallel Supercomputer Implementation of a Biological Inspired Neural Network and its use for Pattern Recognition

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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