high performance computing on graphics processing units: hgpu.org

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Aristotle: A Performance Impact Indicator for the OpenCL Kernels Using Local Memory

Jianbin Fang, Henk Sips, Ana Lucia Varbanescu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Xeon Phi, Local memory, nVidia, OpenCL, Performance, Portability, Tesla C1060, Tesla C2050, Tesla K20

July 29, 2014 by jfang

GPU Computing to Improve Game Engine Performance

Abu Asaduzzaman, Hin Y. Lee

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Tags: Computer science, CUDA, Data parallelism, Games, Image processing, nVidia, nVidia GeForce 8800 GTX, Performance

July 28, 2014 by hgpu

Computational investigation of intense short-wavelength laser interaction with rare gas clusters

Nicolas Bigaouette

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Tags: nVidia, OpenCL, Physics, Quantum Physics, Tesla M2075, Thesis

July 28, 2014 by hgpu

Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the System

Chaitanya P. Chandgude, P. M. Chawan

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Tags: Algorithms, CUDA, Image processing, nVidia

July 28, 2014 by hgpu

Bayesian model comparison via sequential Monte Carlo

Yan Zhou

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Tags: Algorithms, Bayesian, Mathematics, nVidia, nVidia Quadro 2000, OpenCL, Package, Statistics, Thesis

July 28, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

Understanding the ISA impact on GPU Architecture

Mayank Vinodbhai Kothiya

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, PTX, Tesla, Thesis

July 28, 2014 by hgpu

Agent-based crowd simulation using GPU computing

Sean Patrick O'Reilly

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Rendering, Thesis

July 28, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

Brian Hamilton, Stefan Bilbao, Craig J. Webb

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Tags: Acoustics, CUDA, Finite difference, Navier-Stokes equations, NSEs, nVidia, Physics, Tesla K20, Wave equation

July 28, 2014 by hgpu

CUDT: A CUDA Based Decision Tree Algorithm

Win-Tsung Lo, Yue-Shan Chang, Ruey-Kai Sheu, Chun-Chieh Chiu, Shyan-Ming Yuan

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Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 9800 GT

July 28, 2014 by hgpu

Towards fast and certified multiple-precision libraries

Valentina Popescu

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Tags: Algorithms, Computer science, CUDA, Extended precision, nVidia, Tesla C2075, Thesis

July 26, 2014 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

Programming

Aristotle: A Performance Impact Indicator for the OpenCL Kernels Using Local Memory

GPU Computing to Improve Game Engine Performance

Computational investigation of intense short-wavelength laser interaction with rare gas clusters

Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the System

Bayesian model comparison via sequential Monte Carlo

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Understanding the ISA impact on GPU Architecture

Agent-based crowd simulation using GPU computing

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

CUDT: A CUDA Based Decision Tree Algorithm

Towards fast and certified multiple-precision libraries

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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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