high performance computing on graphics processing units: hgpu.org

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Parallel view-dependent refinement of progressive meshes

Liang Hu, Pedro V. Sander, Hugues Hoppe

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Tags: Computer science, HLSL, nVidia, nVidia GeForce 8800 GTX, Triangular meshes, Visualization

November 6, 2010 by hgpu

Magnetohydrodynamics simulations on graphics processing units

Hon-Cheng Wong, Un-Hong Wong, Xueshang Feng, Zesheng Tang

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Tags: Computational Physics, CUDA, Electrodynamics, Magnetohydrodynamics, nVidia, nVidia GeForce GTX 295, Physics

November 6, 2010 by hgpu

SAPPORO: A way to turn your graphics cards into a GRAPE-6

Evghenii Gaburov, Stefan Harfst, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 9800 GX2, Package, Physics

November 6, 2010 by hgpu

PacketShader: a GPU-accelerated software router

Sangjin Han, Keon Jang, KyoungSoo Park, Sue Moon

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Tags: Computer science, CUDA, Network communications, nVidia, nVidia GeForce GTX 480, Software router

November 6, 2010 by hgpu

An Introduction to GPU Accelerated Surgical Simulation

Thomas S. Sorensen, Jesper Mosegaard

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Tags: ATI, ATI Radeon X1900, Medicine, nVidia, nVidia GeForce 7900 GTX, OpenGL, Surgical simulation

November 5, 2010 by hgpu

Multi-Level Graph Layout on the GPU

Yaniv Frishman, Ayellet Tal

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Tags: Cg, Computer science, Graph layout, nVidia, nVidia GeForce 8800 GTS, OpenGL

November 5, 2010 by hgpu

GPU’s for event reconstruction in the FairRoot framework

M. {Al-Turany}, F. {Uhlig}, R. {Karabowicz}

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Tags: CUDA, Instrumentation and measurement, Nuclear physics, nVidia, Package, Particle physics and field theory, Physics, Tesla C1060

November 5, 2010 by hgpu

The GPU as numerical simulation engine

J. Bolz, I. Farmer, E. Grinspun, P. Schroder

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Tags: Computer science, Fluid simulation, Navier-Stokes equations, NSEs, Numerical simulation, nVidia, Sparse matrix

November 5, 2010 by hgpu

Clustering billions of data points using GPUs

Ren Wu, Bin Zhang, Meichun Hsu

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 280

November 5, 2010 by hgpu

On Dynamic Load Balancing on Graphics Processors

Daniel Cederman, Philippas Tsigas

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 9600 GT, Optimization, Performance

November 5, 2010 by hgpu

Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA

Ogier Maitre, Laurent A. Baumes, Nicolas Lachiche, Avelino Corma, Pierre Collet

Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Optimization

November 5, 2010 by hgpu

MPI within a GPU

Bobby Dalton Young

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Tags: Computer science, CUDA, Data parallelism, MPI, nVidia, nVidia GeForce 8800 GTS, Thesis, Virtualization

November 5, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

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high performance computing on graphics processing units: hgpu.org

Parallel view-dependent refinement of progressive meshes

Magnetohydrodynamics simulations on graphics processing units

SAPPORO: A way to turn your graphics cards into a GRAPE-6

PacketShader: a GPU-accelerated software router

An Introduction to GPU Accelerated Surgical Simulation

Multi-Level Graph Layout on the GPU

GPU’s for event reconstruction in the FairRoot framework

The GPU as numerical simulation engine

Clustering billions of data points using GPUs

On Dynamic Load Balancing on Graphics Processors

Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA

MPI within a GPU

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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

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