high performance computing on graphics processing units: hgpu.org

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APEnet+: high bandwidth 3D torus direct network for petaflops scale commodity clusters

Roberto Ammendola, Andrea Biagioni, Ottorino Frezza, Francesca Lo Cicero, Alessandro Lonardo, Pier Stanislao Paolucci, Davide Rossetti, Andrea Salamon, Gaetano Salina, Francesco Simula, Laura Tosoratto, Piero Vicini

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Tags: Computational Physics, Distributed computing, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, OpenMPI, Physics, QCD, Tesla C1060, Tesla M2050

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

XMalloc: A Scalable Lock-free Dynamic Memory Allocator for Many-core Machines

Xiaohuang Huang, Christopher I. Rodrigues, Stephen Jones, Ian Buck, Wen-mei Hwu

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Tags: Algorithms, Computer science, CUDA, Memory, Memory model, nVidia, Tesla C1060

February 20, 2011 by hgpu

Accelerating Particle Image Velocimetry Using Hybrid Architectures

Vivek Venugopal, Cameron D. Patterson, Kevin Shinpaugh

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Tags: Computer science, CUDA, FPGA, nVidia, Tesla C1060, Visualization

February 19, 2011 by hgpu

Efficiency Considerations of Cauchy Reed-Solomon Implementations on Accelerator and Multi-Core Platforms

Thomas Steinke, Kathrin Peter, and Sebastian Borchert

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Tags: Cell processor, Computer science, CUDA, Error recovery, FPGA, nVidia, Tesla C1060, Tesla C870

February 19, 2011 by hgpu

Optimization of HEP codes on GPUs

M. Al-Turany

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Tags: CUDA, High Energy Physics - Experiment, nVidia, nVidia GeForce 8400 GT, nVidia GeForce 8800 GT, nVidia GeForce GTX 480, nVidia Quadro NVS 290, Optimization, Physics, Tesla C1060

February 18, 2011 by hgpu

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

JunKyu Lee, Junqing Sun, Gregory D. Peterson, Robert J. Harrison, Robert J. Hinde

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

February 18, 2011 by hgpu

Accelerating Double Precision Floating-point Hessenberg Reduction on FPGA and Multicore Architectures

Miaoqing Huang, Lingyuan Wang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, Extended precision, FPGA, nVidia, nVidia GeForce GTX 480, OpenMP, Performance, Tesla C1060

February 18, 2011 by hgpu

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Pei-Hung Lin, Jagan Jayaraj, and Paul R. Woodward

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Tags: Cell processor, Code generation, Compilers, Computer science, CUDA, Fortran, High-level Languages, Memory model, nVidia, Tesla C1060

February 17, 2011 by hgpu

Enhancing the simulation of P systems for the SAT problem on GPUs

J.M. Cecilia, J.M. Garcia, G.D. Guerrero, M.A. Martinez-Amor, M.J. Perez-Jimenez, M. Ujaldon

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Tags: Biology, CUDA, nVidia, P systems, SAT, Tesla C1060

February 16, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

David Dewayne Jenkins

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce 8600 M, Stochastic simulation, Tesla C1060, Tesla C870, Thesis

February 16, 2011 by hgpu

GPU Accelerated Stochastic Simulation

David D. Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Stochastic simulation, Tesla C1060

February 16, 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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

APEnet+: high bandwidth 3D torus direct network for petaflops scale commodity clusters

Final Project Implementing Extremely Randomized Trees in CUDA

XMalloc: A Scalable Lock-free Dynamic Memory Allocator for Many-core Machines

Accelerating Particle Image Velocimetry Using Hybrid Architectures

Efficiency Considerations of Cauchy Reed-Solomon Implementations on Accelerator and Multi-Core Platforms

Optimization of HEP codes on GPUs

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

Accelerating Double Precision Floating-point Hessenberg Reduction on FPGA and Multicore Architectures

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Enhancing the simulation of P systems for the SAT problem on GPUs

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

GPU Accelerated Stochastic Simulation

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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