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Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Martin Lucke

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 1080, OpenCL, Partial differential equations, PDEs, performance portability, Thesis

January 27, 2019 by hgpu

AMGCL: an Efficient, Flexible, and Extensible Algebraic Multigrid Implementation

Denis Demidov

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Tags: Computer science, CUDA, Differential equations, Mathematical Software, multigrid, nVidia, OpenCL, OpenMP, Package, Partial differential equations, PDEs, Tesla K80

November 18, 2018 by hgpu

cuPentBatch – A batched pentadiagonal solver for NVIDIA GPUs

Andrew Gloster, Lennon O Naraigh, Khang Ee Pang

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Tags: Computational Physics, CUDA, Differential equations, nVidia, nVidia GeForce GTX Titan X, Package, Partial differential equations, PDEs, Physics

July 21, 2018 by hgpu

Computing dynamics of thin films via large scale GPU-based simulations

Michael-Angelo Y.-H. Lam, Linda J. Cummings, Lou Kondic

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Tags: cfd, CUDA, Differential equations, Fluid dynamics, Liquid crystals, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs

June 28, 2018 by hgpu

Long-time Simulations with Complex Code Using Multiple Nodes of Intel Xeon Phi Knights Landing

Jonathan S. Graf, Matthias K. Gobbert, Samuel Khuvis

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Tags: Computer science, Differential equations, Intel Xeon Phi, MPI, OpenMP, Partial differential equations, PDEs

February 17, 2018 by hgpu

GPU Accelerated Finite Element Assembly with Runtime Compilation

Tao Cui, Xiaohu Guo, Hui Liu

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Partial differential equations, PDEs, Symbolic Computation, Tesla K20, Tesla M2090, Tesla V100

February 15, 2018 by hgpu

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Lukas Polok

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Tags: Algorithms, Computer science, Differential equations, Factorization, FEM, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla K40, Thesis

December 19, 2017 by hgpu

A performance spectrum for parallel computational frameworks that solve PDEs

J. Chang, K. B. Nakshatrala, M. G. Knepley, L. Johnsson

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Tags: Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, MPI, Partial differential equations, PDEs

June 1, 2017 by hgpu

Fast GPU-Based Seismogram Simulation from Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

Saptarshi Das, Xi Chen, Michael P. Hobson

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Tags: CUDA, Differential equations, Earth and Space Sciences, Geophysics, Heterogeneous systems, nVidia, Partial differential equations, PDEs, Seismology, Spectral methods, Tesla C2075, Tesla K20, Visualization, Wave equation

May 18, 2017 by hgpu

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

Daniel J Magee, Kyle E Niemeyer

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Tags: Algorithms, cfd, Computational Physics, CUDA, Differential equations, Fluid dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Tesla K40

May 11, 2017 by hgpu

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

J.E. Adsuara, I. Cordero-Carrion, P. Cerda-Duran, M.A. Aloy

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Tags: CUDA, Differential equations, Finite difference, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs, Tesla K40

May 2, 2017 by hgpu

OpenCL-Based FPGA Accelerator for 3D FDTD with Periodic and Absorbing Boundary Conditions

Hasitha Muthumala Waidyasooriya, Tsukasa Endo, Masanori Hariyama, Yasuo Ohtera

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Tags: Computer science, Differential equations, FDTD, Finite difference, Finite-difference time-domain, FPGA, OpenCL, Partial differential equations, PDEs

April 26, 2017 by hgpu

IPMACC: a framework for translating OpenACC for C API to CUDA, OpenCL, and Intel ISPC

Loop Perforation in OpenACC

multiQueryStream: Concurrent query processing in a GPU-based database system

Concurrent query processing in a GPU-based database system

SYCL-DNN: The SYCL-DNN neural network acceleration library

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

SYCL-BLAS: An implementation of BLAS using the SYCL open standard for acceleration on OpenCL devices

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

The Study of the OpenCL Processing Models for the FPGA Device

The Study of the OpenCL Processing Models for the FPGA Devices

TonY: a framework to natively run deep learning frameworks on Apache Hadoop

TonY: An Orchestrator for Distributed Machine Learning Jobs

fairseq: Facebook AI Research Sequence-to-Sequence Toolkit written in Python

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

mARGOt: Dynamic Application Autotuning for Self-Aware Approximate Computing

Dynamic Application Autotuning for Self-Aware Approximate Computing

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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

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