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A Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

William R. Saunders, James Grant, Eike H. Muller

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Tags: Algorithms, Biology, Chemistry, Code generation, Computer science, CUDA, Differential equations, DSL, Molecular dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Python, Tesla K20

April 15, 2017 by hgpu

Parallel Level set algorithm with MPI and accelerated on GPU

Zhenlin Wang

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Tags: Computational Physics, CUDA, Finite difference, MPI, nVidia, Package, PDEs, Physics

December 17, 2016 by hgpu

A Performance Model and Optimization Strategies for Automatic GPU Code Generation of PDE Systems Described by a Domain-Specific Language

Yue Hu

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Tags: Code generation, Computer science, CUDA, DSL, Fluid dynamics, Intel Xeon Phi, nVidia, OpenCL, Package, PDEs, PTX, Stencil computation, Tesla K20, Thesis

August 31, 2016 by hgpu

Finite Element Integration with Quadrature on the GPU

Matthew G. Knepley, Karl Rupp, Andy R. Terrel

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Tags: AMD FirePro W9100, ATI, Computer science, Differential equations, Mathematical Software, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 750 Ti, OpenCL, Partial differential equations, PDEs, Tesla K20

July 16, 2016 by hgpu

A Problem-Based Learning Approach to GPU Computing

Robert Geist, Joshua A. Levine, James Westall

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX Titan X, OpenCL, Partial differential equations, PDEs

November 29, 2015 by hgpu

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, S. Rajamanickam

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Tags: Computer science, CUDA, Differential equations, nVidia, OpenMP, Partial differential equations, PDEs, Tesla K20

November 24, 2015 by hgpu

Evaluating 3-D Stencil codes on Intel Xeon Phi: Limitations and Trade-offs

Mario Hernandez, Juan M. Cebrian, Jose M. Cecilia, Jose M. Garcia

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Tags: Algorithms, Computer science, Differential equations, Intel Xeon Phi, OpenMP, Partial differential equations, PDEs, Wave equation

November 11, 2015 by hgpu

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Lukas Einkemmer

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Tags: Computer science, CUDA, Differential equations, Intel Xeon Phi, nVidia, Partial differential equations, PDEs, Performance, Tesla K80

November 10, 2015 by hgpu

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Hector Dearman

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Tags: Benchmarking, Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, nVidia GRID K520, OpenCL, Partial differential equations, PDEs, Thesis

November 3, 2015 by hgpu

Toward a Multi-level Parallel Framework on GPU Cluster with PetSC-CUDA for PDE-based Optical Flow Computation

S. Cuomo, A. Galletti, G. Giunta, L. Marcellino

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Tags: Algorithms, Computer science, CUDA, Differential equations, GPU cluster, Heterogeneous systems, nVidia, nVidia Quadro K5000, Optical flow, Partial differential equations, PDEs

June 24, 2015 by hgpu

A Parallel Implementation of the Galerkin Method for Solving Partial Differential Equations on a Triangular Mesh

Rachel N. Hess

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Tags: Differential equations, FEM, Finite element method, Mathematics, OpenCL, Partial differential equations, PDEs, PyOpenCL, Thesis, Triangular meshes

June 7, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 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 Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

Parallel Level set algorithm with MPI and accelerated on GPU

A Performance Model and Optimization Strategies for Automatic GPU Code Generation of PDE Systems Described by a Domain-Specific Language

Finite Element Integration with Quadrature on the GPU

A Problem-Based Learning Approach to GPU Computing

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

Evaluating 3-D Stencil codes on Intel Xeon Phi: Limitations and Trade-offs

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Toward a Multi-level Parallel Framework on GPU Cluster with PetSC-CUDA for PDE-based Optical Flow Computation

A Parallel Implementation of the Galerkin Method for Solving Partial Differential Equations on a Triangular Mesh

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

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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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