high performance computing on graphics processing units: hgpu.org

Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 780 Ti, Package, Physics, Python

June 17, 2015 by hgpu

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Christopher D. Cooper, Lorena A. Barba

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Tags: Biomolecules, Boltzmann equation, Computational Physics, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

June 14, 2015 by hgpu

Blocks and Fuel: Frameworks for deep learning

Bart van Merrienboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, MPI, Neural networks, nVidia, Package, Python, Symbolic Computation, Visualization

June 5, 2015 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

A General Framework for Constrained Bayesian Optimization using Information-based Search

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Partitioning Large Scale Deep Belief Networks Using Dropout

VisPy: Harnessing The GPU For Fast, High-Level Visualization

GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

On the use of deep Boltzmann machines for road signs classification

Autotuning OpenACC Work Distribution via Direct Search

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Blocks and Fuel: Frameworks for deep learning

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Over-synchronization in GPU Programs

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

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SHMT: The Simultaneous and Heterogenous Multithreading project

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