high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications

Parallel execution of a parameter sweep for molecular dynamics simulations in a hybrid GPU/CPU environment

Emmanuel N. Millan, Carlos Garcia Garino, Eduardo M. Bringa

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Tags: Chemistry, CUDA, Molecular dynamics, nVidia, OpenMPI, Package, Ruby, Tesla C2050

November 10, 2012 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 by hgpu

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

Mads Ruben Burgdorff Kristensen, Simon Andreas Frimann Lund, Troels Blum, Brian Vinter

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Tags: Computer science, OpenCL, Optimization, Package, Programming Languages, Python

November 5, 2012 by hgpu

DL: A data layout transformation system for heterogeneous computing

I-Jui Sung, Geng Daniel Liu, Wen-Mei W. Hwu

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Package

November 1, 2012 by hgpu

Silhouette Extraction using Graphics Processing Units

Kristian Haga Karstensen

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Tags: Algorithms, Computer vision, Image processing, nVidia, nVidia GeForce GTX 460, OpenCL, Optimization, Package, Thesis

October 29, 2012 by hgpu

Analysis & Design of Efficient Cryptographic Systems

Michael Lehmann

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package, Security, Stream Ciphers

October 28, 2012 by hgpu

BrainCove: A Tool for Voxel-wise fMRI Brain Connectivity Visualization

A.F. van Dixhoorn, J. Milles, B. van Lew, C.P. Botha

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Tags: Computer science, Filtering, Image generation, MRI, OpenCL, OpenGL, Package, Rendering, Visualization

October 26, 2012 by hgpu

Automatic Generation Of Application-Specific Accelerators for FPGAs from Python Loop Nests

David Sheffield, Michael Anderson, Kurt Keutzer

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Tags: Computer science, Design space exploration, FPGA, Package, Python

October 25, 2012 by hgpu

GPUSync: A Framework for Real-Time GPU Management

Glenn A. Elliott, Bryan C. Ward, James H. Anderson

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 470, Package, Performance

October 23, 2012 by hgpu

A short guide to CUDA C: For physicists with multi-core graphics cards

David Plotzki

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia Quadro NVS 3100 M, Package, Physics, Tesla C1060, Tutorial

October 19, 2012 by hgpu

AeminiumGPU: An Intelligent Framework for GPU Programming

Alcides Fonseca, Bruno Cabral

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Tags: Computer science, Heterogeneous systems, Java, MapReduce, nVidia, nVidia GeForce GTX 285, OpenCL, Package

October 13, 2012 by hgpu

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

M. Prato, R. Cavicchioli, L. Zanni, P. Boccacci, M. Bertero

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Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, Numerical Analysis, nVidia, nVidia GeForce GTX 280, Package

October 9, 2012 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

Packages

Parallel execution of a parameter sweep for molecular dynamics simulations in a hybrid GPU/CPU environment

GPU Virtualization

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

DL: A data layout transformation system for heterogeneous computing

Silhouette Extraction using Graphics Processing Units

Analysis & Design of Efficient Cryptographic Systems

BrainCove: A Tool for Voxel-wise fMRI Brain Connectivity Visualization

Automatic Generation Of Application-Specific Accelerators for FPGAs from Python Loop Nests

GPUSync: A Framework for Real-Time GPU Management

A short guide to CUDA C: For physicists with multi-core graphics cards

AeminiumGPU: An Intelligent Framework for GPU Programming

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

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Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

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

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