high performance computing on graphics processing units: hgpu.org

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Scalable GPU Acceleration of B-Spline Signal Processing Operations

Alexander Karantza

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Tags: CUDA, nVidia, Signal processing, Tesla C2070, Thesis

October 13, 2012 by hgpu

Fast Parallel Implementation of Fractional Packing and Covering Linear Programs

Slobodan Jelic, Soren Laue, Domagoj Matijevic, Patrick Wijerama

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Tags: Algorithms, CUDA, Mathematics, nVidia, Tesla C2070

October 13, 2012 by hgpu

.NET High Performance Computing

Hsuan-Hsiu Ou

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 440, nVidia GeForce GTX 480, Task scheduling, Thesis

October 13, 2012 by hgpu

FPGA-GPU-CPU Heterogenous Architecture for Real-time Cardiac Physiological Optical Mapping

Pingfan Meng, Matthew Jacobsen, Ryan Kastner

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Tags: Algorithms, CUDA, FPGA, Image processing, Medicine, nVidia, nVidia GeForce GTX 590

October 13, 2012 by hgpu

Parallel H-Tree Based Data Cubing on Graphics Processors

Baoyuan Wang, Yizhou Yu

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX

October 13, 2012 by hgpu

Programming NVIDIA cards by means of transitive closure based parallelization algorithms

Marek Palkowski, Wlodzimierz Bielecki

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Tags: Computer science, CUDA, nVidia, Performance, Tesla S1070

October 13, 2012 by hgpu

Mesh Independent Loop Fusion for Unstructured Mesh Applications

Carlo Bertolli, Adam Betts, Gihan R. Mudalige, Paul H.J. Kelly, Michael B. Giles

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Tags: Computer science, CUDA, nVidia, Programming techniques, Tesla M2050

October 13, 2012 by hgpu

GPU-Based Local-Dimming for Power Efficient Imaging

Chihao Xu, Michael Krause, Jens Kruger

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Tags: Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 555 M

October 13, 2012 by hgpu

Automatic Parallelization of Tiled Loop Nests with Enhanced Fine-Grained Parallelism on GPUs

Peng Di, Ding Ye, Yu Su, Yulei Sui, Jingling Xue

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050

October 13, 2012 by hgpu

Accelerating Mean Shift Segmentation Algorithm on Hybrid CPU/GPU Platforms

Liang Men, Miaoqing Huang, John Gauch

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Tags: Algorithms, Clustering, CUDA, Image processing, nVidia, Tesla C2075

October 9, 2012 by hgpu

A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries

Salvatore Cuomo, Pasquale De Michele, Raffaele Farina, Marta Chinnici

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Tags: CUDA, Earth and Space Sciences, Mathematics, Numerical Analysis, nVidia, Tesla S2050

October 9, 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

Scalable GPU Acceleration of B-Spline Signal Processing Operations

Fast Parallel Implementation of Fractional Packing and Covering Linear Programs

.NET High Performance Computing

FPGA-GPU-CPU Heterogenous Architecture for Real-time Cardiac Physiological Optical Mapping

Parallel H-Tree Based Data Cubing on Graphics Processors

Programming NVIDIA cards by means of transitive closure based parallelization algorithms

Mesh Independent Loop Fusion for Unstructured Mesh Applications

GPU-Based Local-Dimming for Power Efficient Imaging

Automatic Parallelization of Tiled Loop Nests with Enhanced Fine-Grained Parallelism on GPUs

Accelerating Mean Shift Segmentation Algorithm on Hybrid CPU/GPU Platforms

A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries

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

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