high performance computing on graphics processing units: hgpu.org

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A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Evaluation of Standardized Password-based Key Derivation against Parallel Processing Platforms

Markus Durmuth, Tim Guneysu, Markus Kasper, Christof Paar, Tolga Yalcin, Ralf Zimmermann

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Tags: Computer science, CUDA, FPGA, GPU cluster, nVidia, Review, Security, Tesla C2070

February 14, 2013 by hgpu

A Multi-GPU Sources Reconstruction Method for Imaging Applications

Miguel Lopez-Portugues, Yuri Alvarez, Jesus A. Lopez-Fernandez, Cebrian Garcia, Rafael G. Ayestaran, Fernando Las-Heras

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Tags: CUDA, Electrodynamics, GPU cluster, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 680, Signal processing

February 6, 2013 by hgpu

Efficient Implementation of MrBayes on multi-GPU

Jie Bao, Hongju Xia, Jianfu Zhou, Xiaoguang Liu, Gang Wang

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Tags: Bayesian, Biology, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 480, Package, Task scheduling

January 28, 2013 by hgpu

A Multi-GPU Programming Library for Real-Time Applications

Sebastian Schaetz, Martin Uecker

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Tags: Algorithms, CUDA, GPU cluster, Image reconstruction, Magnetic resonance imaging, MPI, MRI, nVidia, nVidia GeForce GTX 580, Performance, Signal processing

January 8, 2013 by hgpu

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

George Teodoro, Tony Pan, Tahsin M. Kurc, Jun Kong, Lee A. D. Cooper, Norbert Podhorszki, Scott Klasky, Joel H. Saltz

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Tags: CUDA, GPU cluster, Image processing, Microscopy, nVidia, Prefetch, Tesla M2090

January 6, 2013 by hgpu

Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Qing Hou, Min Li, Yulu Zhou, Jiechao Cui, Zhenguo Cui, Jun Wang

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Tags: Computational Physics, CUDA, GPU cluster, Materials Science, Molecular dynamics, nVidia, Physics, Tesla C2050

January 2, 2013 by hgpu

Coulomb, Landau and Maximally Abelian Gauge Fixing in Lattice QCD with Multi-GPUs

Mario Schrock, Hannes Vogt

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Mixed precision, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla C2070

December 23, 2012 by hgpu

IceCubes GPGPU’s cluster for extensive MC production

Martin Merck, Dmitry Chirkin, Juan Carlos Diaz Velez, Heath Skarlupka

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Tags: Computational Physics, CUDA, GPU cluster, Monte Carlo simulation, Nuclear physics, nVidia, Particle physics and field theory, Physics, Raytracing, Tesla M2070

December 20, 2012 by hgpu

A Static Load Balancing Scheme for Parallel Volume Rendering on Multi-GPU Clusters

Shusen Liu, Venkatram Vishwanath, Joseph Insley, Mark Hereld, Michael E. Papka, Valerio Pascucci

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Tags: Computer science, CUDA, GPU cluster, nVidia, Rendering, Tesla M2070

December 14, 2012 by hgpu

Multi-level Parallelism for Incompressible Flow Computations on GPU Clusters

Dana A. Jacobsen, Inanc Senocak

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Tags: Computer science, CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, Tesla C1060, Tesla S1070

December 12, 2012 by hgpu

ValuePack: value-based scheduling framework for CPU-GPU clusters

Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar

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

November 21, 2012 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

See all packages

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high performance computing on graphics processing units: hgpu.org

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Evaluation of Standardized Password-based Key Derivation against Parallel Processing Platforms

A Multi-GPU Sources Reconstruction Method for Imaging Applications

Efficient Implementation of MrBayes on multi-GPU

A Multi-GPU Programming Library for Real-Time Applications

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Coulomb, Landau and Maximally Abelian Gauge Fixing in Lattice QCD with Multi-GPUs

IceCubes GPGPU’s cluster for extensive MC production

A Static Load Balancing Scheme for Parallel Volume Rendering on Multi-GPU Clusters

Multi-level Parallelism for Incompressible Flow Computations on GPU Clusters

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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