high performance computing on graphics processing units: hgpu.org

hgpu.org » Fortran

Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control

Sergei Morozov, Sudhanshu Mathur

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Tags: CUDA, Finance, Fortran, Machine learning, nVidia, nVidia GeForce GTX 280, Package

October 21, 2011 by hgpu

OpenMP for Accelerators

James C. Beyer, Eric J. Stotzer, Alistair Hart, Bronis R. de Supinski

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Tags: Computer science, CUDA, DSP, Fortran, nVidia, OpenMP, Tesla C2050

October 21, 2011 by hgpu

FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm

P. Hanappe, A. Beurive, F. Laguzet, L. Steels, N. Bellouin, O. Boucher, Y. H. Yamazaki, T. Aina, M. Allen

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Tags: Algorithms, Cell processor, Earth and Space Sciences, Fortran, nVidia, nVidia GeForce GT 330 M, OpenCL, Weather prediction, Weather Prediction Model

October 20, 2011 by hgpu

Experience Applying Fortran GPU Compilers to Numerical Weather Prediction

T. Henderson, J. Middlecoff, J. Rosinski, M. Govett, P. Madden

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Tags: CUDA, Earth and Space Sciences, Fortran, nVidia, nVidia GeForce GTX 280, Tesla C2050, Weather prediction

October 18, 2011 by hgpu

Magneto-hydrodynamics simulation in astrophysics

Bijia Pang

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Tags: Algorithms, Astrophysics, CUDA, Fortran, Heterogeneous systems, Magnetohydrodynamics, nVidia, OpenCL, Physics, Tesla C1060, Tesla C2050, Thesis

October 17, 2011 by hgpu

Performance Comparison with OpenMP Parallelization for Multi-core Systems

Chao-Tung Yang, Tzu-Chieh Chang, Hsien-Yi Wang, William C.C. Chu, Chih-Hung Chang

Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Fortran, nVidia, OpenCL, OpenMP, Performance

August 8, 2011 by hgpu

An auto-tuning framework for parallel multicore stencil computations

Shoaib Kamil, Cy Chan, Leonid Oliker, John Shalf, Samuel Williams

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Tags: Code generation, Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 280

July 18, 2011 by hgpu

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Matthew J. Sottile, Craig E Rasmussen, Wayne N. Weseloh, Robert W. Robey, Daniel Quinlan, Jeffrey Overbey

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Tags: Computer science, Fortran, nVidia, OpenCL, Package, Programming Languages, Tesla C2050

July 14, 2011 by hgpu

Acceleration of the GAMESS-UK electronic structure package on graphical processing units

Karl A. Wilkinson, Paul Sherwood, Martyn F. Guest, Kevin J. Naidoo

Tags: Chemistry, Fortran, Molecular dynamics, Molecular modeling, nVidia

May 21, 2011 by hgpu

An algorithmic incremental and iterative development method to parallelize dusty-deck FORTRAN HPC codes in GPGPUs using CUDA

N. Ghaemian, M. Sharifi, B. Minaei,R. Orujov

Tags: Computer science, CUDA, Fortran, High-level Languages, nVidia

April 6, 2011 by hgpu

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Pei-Hung Lin, Jagan Jayaraj, and Paul R. Woodward

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Tags: Cell processor, Code generation, Compilers, Computer science, CUDA, Fortran, High-level Languages, Memory model, nVidia, Tesla C1060

February 17, 2011 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

Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control

OpenMP for Accelerators

FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm

Experience Applying Fortran GPU Compilers to Numerical Weather Prediction

Magneto-hydrodynamics simulation in astrophysics

Performance Comparison with OpenMP Parallelization for Multi-core Systems

An auto-tuning framework for parallel multicore stencil computations

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Acceleration of the GAMESS-UK electronic structure package on graphical processing units

An algorithmic incremental and iterative development method to parallelize dusty-deck FORTRAN HPC codes in GPGPUs using CUDA

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

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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