high performance computing on graphics processing units: hgpu.org

hgpu.org » Fortran

Overlapping Computation and Communication for Advection on Hybrid Parallel Computers

James B White III (Trey), Jack Dongarra

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Tags: CUDA, Fluid dynamics, Fortran, GPU cluster, Hybrid computing, MPI, nVidia, OpenMP, OpenMPI, Presentation, Tesla C1060, Tesla C2050

November 27, 2011 by hgpu

Seismic Wave Propagation Simulation Using Accelerated Support Operator Rupture Dynamics on Multi-GPU

Yichen Zhou, Shenyi Song, Tingxing Dong, David A. Yuen

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Tags: CUDA, Earth and Space Sciences, Finite difference, Fortran, Geoscience, MPI, nVidia, Seismic modeling, Tesla C1060

November 14, 2011 by hgpu

Gyrofluid Modeling of Turbulent, Kinetic Physics

Kate Marie Despain

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Tags: CUDA, Fortran, MPI, nVidia, nVidia GeForce 9800 GTX, Package, Physics, Plasma physics

November 4, 2011 by hgpu

A case study on porting scientific applications to GPU/CUDA

Javier Delgado, Joao Gazolla, Esteban Clua, S. Masoud Sadjadi

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Tags: Computer science, CUDA, Earth and Space Sciences, Fortran, nVidia, nVidia GeForce 9300 M, nVidia GeForce 9400 M, Tesla S1070, Weather prediction

October 26, 2011 by hgpu

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

Austen C. Duffy

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Tags: Algorithms, CUDA, Fluid dynamics, Fortran, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Optimization, Partial differential equations, PDEs, Thesis

October 23, 2011 by hgpu

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

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

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high performance computing on graphics processing units: hgpu.org

Overlapping Computation and Communication for Advection on Hybrid Parallel Computers

Seismic Wave Propagation Simulation Using Accelerated Support Operator Rupture Dynamics on Multi-GPU

Gyrofluid Modeling of Turbulent, Kinetic Physics

A case study on porting scientific applications to GPU/CUDA

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

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

Recent source codes

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

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