high performance computing on graphics processing units: hgpu.org

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Accelerating Dust Temperature Calculations with Graphics Processing Units

Patrik Jonsson, Joel Primack

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Physics, Tesla C1060

November 6, 2010 by hgpu

Fast scale invariant feature detection and matching on programmable graphics hardware

Nico Cornelis, Luc Van Gool

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX

November 6, 2010 by hgpu

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Jayram M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alex Veidenbaum

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Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

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

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

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

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

An experimental approach to performance measurement of heterogeneous parallel applications using CUDA

Allen D. Malony,Scott Biersdorff,Wyatt Spear,Shangkar Mayanglambam

Tags: Computer science, CUDA, nVidia, Performance

November 5, 2010 by hgpu

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping

E. Z. Zhang, Y. Jiang, G. Ziyu, X. Shen

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Tags: Compilers, Computer science, CUDA, nVidia, Performance, Programming Languages, Tesla C1060

November 5, 2010 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Accelerating Dust Temperature Calculations with Graphics Processing Units

Fast scale invariant feature detection and matching on programmable graphics hardware

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Magnetohydrodynamics simulations on graphics processing units

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

PacketShader: a GPU-accelerated software router

GPU’s for event reconstruction in the FairRoot framework

Clustering billions of data points using GPUs

On Dynamic Load Balancing on Graphics Processors

MPI within a GPU

An experimental approach to performance measurement of heterogeneous parallel applications using CUDA

Streamlining GPU applications on the fly: thread divergence elimination through runtime thread-data remapping

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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