high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

Hartwig Anzt, Bjorn Rocker, Vincent Heuveline

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Tags: Computer science, Energy-efficient computing, Linear Algebra, Mixed precision, nVidia, Tesla C1060, Tesla S1070

February 22, 2011 by hgpu

Performance analysis and optimization of three-dimensional FDTD on GPU using roofline model

Ki-Hwan Kim, KyoungHo Kim, Q-Han Park

Tags: Computer science, CUDA, FDTD, Finite-difference time-domain, nVidia, nVidia GeForce GTX 480

February 22, 2011 by hgpu

Data Structures and Transformations for Physically Based Simulation on a GPU

Perhaad Mistry, Dana Schaa, Byunghyun Jang, David Kaeli, Albert Dvornik, Dwight Meglan

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, Physics-based simulation

February 22, 2011 by hgpu

Parallel power flow solutions using a biconjugate gradient algorithm and a Newton method: A GPU-based approach

Norberto Garcia

Tags: Computational Engineering, Computer science, Conjugate gradient solver

February 22, 2011 by hgpu

Software-Based ECC for GPUs

Naoya Maruyama, Akira Nukada, Satoshi Matsuoka

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Tags: Computer science, CUDA, Error recovery, FFT, N-body simulation, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 285, Tesla S1070

February 21, 2011 by hgpu

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Kanupriya Gulati and Sunil P Khatri

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280

February 21, 2011 by hgpu

A massively parallel framework using P systems and GPUs

Jose M. Cecilia, Gines D. Guerrero, Jose M. Garcia, Miguel A. Martinez-del-Amor, Ignacio Perez-Hurtado, Mario J. Perez-Jimenez

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Tags: Biology, Computer science, CUDA, nVidia, P systems, Tesla C1060

February 21, 2011 by hgpu

GPU Acceleration of Equations Assembly in Finite Elements Method – Preliminary Results

Jiri Filipovic, Igor Peterlik, Jan Fousek

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Tags: Computer science, CUDA, Finite element method, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

February 21, 2011 by hgpu

Data parallel loop statement extension to CUDA: GpuC

Zeki Bozkus, Rajeev Thakur, William Gropp, Ewing Lusk

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization

February 21, 2011 by hgpu

Final Project Implementing Extremely Randomized Trees in CUDA

Michael A. Geary, HyoukJoong Lee, Davide Signorelli, Jordan Vaughan

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, OpenMP, Tesla C1060

February 20, 2011 by hgpu

Architecting graphics processors for non-graphics compute acceleration

Tor M. Aamodt

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Tags: Computer science, Hardware Architecture, nVidia, Review

February 20, 2011 by hgpu

Design Space Exploration for GPU-Based Architecture

Zhenyu Ye

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Tags: Computer science, CUDA, Factorization, Hardware Architecture, Memory model, nVidia, nVidia GeForce 8800 GTX, Review, Thesis

February 20, 2011 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

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high performance computing on graphics processing units: hgpu.org

Applications

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

Performance analysis and optimization of three-dimensional FDTD on GPU using roofline model

Data Structures and Transformations for Physically Based Simulation on a GPU

Parallel power flow solutions using a biconjugate gradient algorithm and a Newton method: A GPU-based approach

Software-Based ECC for GPUs

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

A massively parallel framework using P systems and GPUs

GPU Acceleration of Equations Assembly in Finite Elements Method – Preliminary Results

Data parallel loop statement extension to CUDA: GpuC

Final Project Implementing Extremely Randomized Trees in CUDA

Architecting graphics processors for non-graphics compute acceleration

Design Space Exploration for GPU-Based Architecture

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Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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