high performance computing on graphics processing units: hgpu.org

hgpu.org » Fortran

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Michail Alvanos, Theodoros Christoudias

View

Download (PDF)

Source codes

Tags: Chemistry, Code generation, CUDA, Earth and Space Sciences, Fortran, nVidia, Package, Tesla M2070

May 2, 2017 by hgpu

Sparse Matrix-Vector Multiplication on GPGPUs

Salvatore Filippone, Valeria Cardellini, Davide Barbieri, Alessandro Fanfarillo

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 660, Package, Review, Sparse matrix, Tesla K20, Tesla K40, Tesla M2070

April 3, 2017 by hgpu

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

Mark Govett, Jim Rosinski, Jacques Middlecoff, Tom Henderson, Jin Lee, Alexander MacDonald, Paul Madden, Julie Schramm, Antonio Duarte

View

Download (PDF)

Tags: CUDA, Earth and Space Sciences, Fortran, Intel Xeon Phi, nVidia, OpenACC, Tesla K80, Weather prediction, Weather Prediction Model

December 6, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

View

Download (PDF)

Source codes

Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

Tetsuya Takaishi

View

Download (PDF)

Tags: Bayesian, Computational finance, CUDA, Finance, Fortran, nVidia, nVidia GeForce GTX 760, OpenACC

March 29, 2016 by hgpu

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

G.R. Mudalige, I.Z. Reguly, M.B. Giles

View

Download (PDF)

Tags: cfd, Code generation, Computer science, CUDA, Fluid dynamics, Fortran, nVidia, Programming techniques, Tesla K80

February 25, 2016 by hgpu

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

Weylin MacCalla, Sameer Kulkarni

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7850, cfd, Fluid dynamics, Fortran, nVidia, OpenACC, Tesla K40

February 8, 2016 by hgpu

Performance and Productivity of Parallel Python Programming: A study with a CFD Test Case

Achim Basermann, Melven Rohrig-Zollner, Joachim Illmer

View

Download (PDF)

Tags: CUDA, Fluid dynamics, Fortran, nVidia, Performance, Python, Tesla C2075

December 22, 2015 by hgpu

Performance analysis and optimization of a CFD application

Wentao Zhang

View

Download (PDF)

Tags: Finite difference, Fluid dynamics, Fortran, Heterogeneous systems, Intel Xeon Phi, Performance, Thesis

October 18, 2015 by hgpu

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Gunther Lukat, Robi Banerjee

View

Download (PDF)

Source codes

Tags: Astrophysics, CUDA, Fortran, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla C2075

September 26, 2015 by hgpu

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

C. Couder-Castaneda, H. Barrios-Pina, I. Gitler, M. Arroyo

View

Download (PDF)

Tags: Computer science, Fortran, Intel Xeon Phi, nVidia, OpenACC, OpenMP, Performance, Tesla C2070

June 10, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Sparse Matrix-Vector Multiplication on GPGPUs

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

Auto-Vectorizing a Large-scale Production Unstructured-mesh CFD Application

Utilizing GPUs to Accelerate Turbomachinery CFD Codes

Performance and Productivity of Parallel Python Programming: A study with a CFD Test Case

Performance analysis and optimization of a CFD application

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

Loo.py: From Fortran to performance via transformation and substitution rules

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)