high performance computing on graphics processing units: hgpu.org

hgpu.org » Condensed matter

Deep neural networks for direct, featureless learning through observation: the case of 2d spin models

K. Mills, I. Tamblyn

View

Tags: Condensed matter, CUDA, Deep learning, Ising model, Materials Science, Neural networks, nVidia, Phase transition, Physics, Tesla K40

July 2, 2017 by hgpu

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Florencio Balboa Usabiaga, Blaise Delmotte, Aleksandar Donev

View

Tags: Condensed matter, CUDA, nVidia, Package, Physics, pyCUDA, Soft Condensed Matter

December 6, 2016 by hgpu

A hybrid algorithm for parallel molecular dynamics simulations

Chris M. Mangiardi, Ralf Meyer

View

Tags: Condensed matter, Intel Xeon Phi, Materials Science, Molecular dynamics

November 3, 2016 by hgpu

OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross-Pitaevskii equation

Vladimir Loncar, Luis E. Young-S., Srdjan Skrbic, Paulsamy Muruganandam, Sadhan K. Adhikari, Antun Balaz

View

Tags: Condensed matter, CUDA, MPI, nVidia, OpenMP, Package, Physics, Tesla M2090

October 22, 2016 by hgpu

GPU Based Detection of Topological Changes in Voronoi Diagrams

Massimo Bernaschi, Matteo Lulli, Mauro Sbragaglia

View

Tags: Computational Physics, Condensed matter, CUDA, Lattice Boltzmann model, nVidia, Physics, Soft Condensed Matter, Voronoi diagram

July 8, 2016 by hgpu

SGO: An ultrafast engine for atomic structure global optimization by differential evolution

Zhanghui Chen, Lin-Wang Wang

View

Tags: Condensed matter, Differential evolution, Materials Science, nVidia, nVidia GeForce GTX 980

March 12, 2016 by hgpu

Aging in the three-dimensional Random Field Ising Model

Sebastian von Ohr, Markus Manssen, Alexander K. Hartmann

View

Tags: Condensed matter, Intel Xeon Phi, Statistical Mechanics

January 14, 2016 by hgpu

Exact diagonalization of quantum lattice models on coprocessors

Topi Siro, Ari Harju

View

Tags: Condensed matter, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, OpenMP, Physics, Tesla K40

November 4, 2015 by hgpu

Scalable Metropolis Monte Carlo for simulation of hard shapes

Joshua A. Anderson, M. Eric Irrgang, Sharon C. Glotzer

View

Tags: Benchmarking, Chemistry, Condensed matter, CUDA, Monte Carlo simulation, nVidia, Physics, Soft Condensed Matter, Tesla K20

September 17, 2015 by hgpu

A parallel algorithm for implicit depletant simulations

Jens Glaser, Andrew S. Karas, Sharon C. Glotzer

View

Tags: Condensed matter, CUDA, Molecular dynamics, nVidia, Package, Physics, Soft Condensed Matter, Tesla K20, Tesla K80

August 31, 2015 by hgpu

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

Ursula Iturraran-Viveros, Miguel Molero-Armenta

View

Tags: Condensed matter, Instrumentation and measurement, nVidia, OpenCL, Package, Physics, PyOpenCL, Python

August 21, 2015 by hgpu

GPU phase-field lattice Boltzmann simulations of growth and motion of a binary alloy dendrite

T. Takaki, R. Rojas, M Ohno, T. Shimokawabe, T. Aoki

View

Tags: Alloys, Condensed matter, CUDA, Lattice Boltzmann model, Materials Science, nVidia, Physics, Tesla K20

July 3, 2015 by hgpu

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

blockgmf: Block based approaches to Matrix Factorization

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

CU2CL: A prototype CUDA-to-OpenCL source-to-source translator

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

GPU-based Parallel Computation Support for Stan

GPU-based Parallel Computation Support for Stan

PANNA: Properties from Artificial Neural Network Architectures

PANNA: Properties from Artificial Neural Network Architectures

Artifact Evaluation for Novel methodologies for predictable CPU-to-GPU command offloading

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

tvm: Open deep learning compiler stack for cpu, gpu and specialized accelerators

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

picongpu: Particle-in-Cell Simulations for the Exascale Era

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

WCCV: Warp-coherent Condition Vectorization(on top of RV)

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

See all packages

* * *

* * *

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

+

HGPU group © 2010-2019 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: