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Multi-level Parallelization of Advanced Video Coding on Hybrid CPU/GPU Platform

Svetislav Momcilovic, Nuno Roma, Leonel Sousa

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Tags: Algorithms, CUDA, H.264/AVC, Image processing, nVidia, nVidia GeForce GTX 580, Task scheduling, Video encoding

July 10, 2012 by hgpu

Runtime Systems and Scheduling Support for High-End CPU-GPU Architectures

Vignesh Trichy Ravi

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

July 10, 2012 by hgpu

A Generic Library for Stencil Computations

Mauro Bianco, Ugo Varetto

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Mathematical Software, MPI, nVidia, PC cluster, Performance, Tesla M2090

July 10, 2012 by hgpu

A hybrid Hermitian general eigenvalue solver

Raffaele Solca, Thomas C. Schulthess, Azzam Haidar, Stanimire Tomov, Ichitaro Yamazaki, Jack Dongarra

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Tags: Chemistry, Computer science, CUDA, Materials Science, Numerical Analysis, nVidia, Tesla M2090

July 10, 2012 by hgpu

Parallelising the Transfer-Matrix Method using Graphics Processors

Thomas Edwards

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Tags: Computer science, CUDA, nVidia, Tesla C1060, Thesis

July 9, 2012 by hgpu

Performance models for CUDA streams on NVIDIA GeForce series

Juan Gomez-Luna, Jose Maria Gonzalez-Linares, Jose Ignacio Benavides, Nicolas Guil

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Performance

July 9, 2012 by hgpu

Elastically Deformable Models based on the Finite Element Method Accelerated on Graphics Hardware using CUDA

Mickeal Verschoor, Andrei C. Jalba

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 570, Sparse matrix

July 9, 2012 by hgpu

Intensity model with blur effect on GPUs applied to large-scale star simulators

Chao Li, Yun-Quan Zhang, Changwen Zheng, Xiaohui Hu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package

July 9, 2012 by hgpu

Complete PISO and SIMPLE solvers on Graphics Processing Units

Tadeusz Tomczak, Katarzyna Zadarnowska, Zbigniew Koza, Maciej Matyka, Aukasz Miroslaw

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Tags: Algorithms, Computer science, CUDA, Navier-Stokes equations, NSEs, nVidia, Tesla C2070

July 9, 2012 by hgpu

Teaching Parallel Programming Models on a Shallow-Water Code

Alexander Breuer, Michael Bader

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Tags: CUDA, Education, Finite volume method, Fluid dynamics, MPI, nVidia, nVidia Quadro FX 2000, OpenMP, Package

July 8, 2012 by hgpu

GPU-Optimized Molecular Dynamics Simulations

Tyson J. Lipscomb

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Tags: Biology, Biomolecules, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Pseudo-random number generators, Review, RNA, Tesla C2070, Thesis

July 8, 2012 by hgpu

Random Walks for Image Cosegmentation

Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 470, Package

July 7, 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

Multi-level Parallelization of Advanced Video Coding on Hybrid CPU/GPU Platform

A Generic Library for Stencil Computations

A hybrid Hermitian general eigenvalue solver

Parallelising the Transfer-Matrix Method using Graphics Processors

Performance models for CUDA streams on NVIDIA GeForce series

Elastically Deformable Models based on the Finite Element Method Accelerated on Graphics Hardware using CUDA

Intensity model with blur effect on GPUs applied to large-scale star simulators

Complete PISO and SIMPLE solvers on Graphics Processing Units

Teaching Parallel Programming Models on a Shallow-Water Code

GPU-Optimized Molecular Dynamics Simulations

Random Walks for Image Cosegmentation

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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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