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ClusterWatch: Flexible, Lightweight Monitoring for High-end GPGPU Clusters

Magdalena Slawinska, Karsten Schwan, Greg Eisenhauer

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Tags: Computer science, CUDA, GPU cluster, nVidia, Tesla M2090

September 20, 2013 by hgpu

Comprehensive Evaluations of Cone-beam CT dose in Image-guided Radiation Therapy via GPU-based Monte Carlo simulations

Davide Montanari, Enrica Scolari, Chiara Silvestri, Yan J. Graves, Hao Yan, Laura Cervino, Roger Rice, Steve B. Jiang, Xun Jia

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Tags: Computed tomography, CT, CUDA, Medical Physics, Medicine, Monte Carlo simulation, nVidia, nVidia GeForce GTX 590, Physics

September 20, 2013 by hgpu

Rethinking the Union of Computed Tomography Reconstruction and GPGPU Computing

Edward S. Jimenez, Laurel J. Orr

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Tags: Algorithms, Computed tomography, CT, CUDA, Medicine, nVidia, Tesla M2090, Tesla S2090, Tomography

September 20, 2013 by hgpu

Performance analysis of multi-core CPUs and GPU computing on SF-FDTD scheme for third order nonlinear materials and periodic media

Jorge Frances Monllor, Sergio Bleda Perez, Jani Tervo, Cristian Neipp Lopez, Andres Marquez Ruiz, Inmaculada Pascual Villalobos, Augusto Belendez Vazquez

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Tags: CUDA, Electrodynamics, FDTD, FEM, Finite element method, Finite-difference time-domain, nVidia, nVidia GeForce GTX 460, Optics

September 20, 2013 by hgpu

Exponential Integrators on Graphics Processing Units

Lukas Einkemmer, Alexander Ostermann

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Tags: Computer science, CUDA, Differential equations, Numerical Analysis, nVidia, Tesla C1060, Tesla C2075

September 20, 2013 by hgpu

Adjustable GPU Acceleration for Hermitian Eigensystems

Michael T. Garba, Horacio Gonzalez-Velez, Daniel L. Roach

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Tesla C2050

September 18, 2013 by hgpu

Acceleration of recovery simulation on big model using GPU

T. T. Bekibayev, B. K. Assilbekov, U. K. Zhapbasbayev

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti

September 18, 2013 by hgpu

A GPU-based Parallel Procedure for Nonlinear Analysis of Complex Structures Using a Coupled FEM/DEM Approach

Lixiang Wang, Shihai Li, Guoxin Zhang, Zhaosong Ma, Lei Zhang

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Tags: Computer science, CUDA, FEM, Finite element method, Nonlinear analysis, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 670, nVidia GeForce GTX 680

September 18, 2013 by hgpu

A distributed computing approach to improve the performance of the Parallel Ocean Program (v2.1)

B. van Werkhoven, J. Maassen, M. Kliphuis, H. A. Dijkstra, S. E. Brunnabend, M. van Meersbergen, F. J. Seinstra, H. E. Bal

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Tags: CUDA, Distributed computing, Earth and Space Sciences, Geoscience, nVidia, Tesla K20

September 18, 2013 by hgpu

Parallel Motion Estimation Implementation for Different Block Matching Algorithms onto GPGPU

Eduarda Monteiro, Marilena Maule, Felipe Sampaio, Claudio Diniz, Bruno Zatt, Sergio Bampi

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, OpenMP, Video encoding

September 17, 2013 by hgpu

Kokkos: Enabling performance portability across manycore architectures

H. Carter Edwards, Christian R. Trott

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Source codes

Tags: Code generation, Computer science, CUDA, Intel Phi, Molecular dynamics, nVidia, Package, Tesla K20

September 17, 2013 by hgpu

High Throughput Low Latency LDPC Decoding on GPU for SDR Systems

Guohui Wang, Michael Wu, Bei Yin, Joseph R. Cavallaro

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Parity-check codes

September 17, 2013 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

Programming

ClusterWatch: Flexible, Lightweight Monitoring for High-end GPGPU Clusters

Comprehensive Evaluations of Cone-beam CT dose in Image-guided Radiation Therapy via GPU-based Monte Carlo simulations

Rethinking the Union of Computed Tomography Reconstruction and GPGPU Computing

Performance analysis of multi-core CPUs and GPU computing on SF-FDTD scheme for third order nonlinear materials and periodic media

Exponential Integrators on Graphics Processing Units

Adjustable GPU Acceleration for Hermitian Eigensystems

Acceleration of recovery simulation on big model using GPU

A GPU-based Parallel Procedure for Nonlinear Analysis of Complex Structures Using a Coupled FEM/DEM Approach

A distributed computing approach to improve the performance of the Parallel Ocean Program (v2.1)

Parallel Motion Estimation Implementation for Different Block Matching Algorithms onto GPGPU

Kokkos: Enabling performance portability across manycore architectures

High Throughput Low Latency LDPC Decoding on GPU for SDR Systems

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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