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

GPU-accelerated micromagnetic simulations using cloud computing

C. L. Jermain, G. E. Rowlands, R. A. Buhrman, D. C. Ralph

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Tags: Cloud, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 770, nVidia GRID K520, Package, Physics, Python

May 10, 2015 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

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

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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