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Optimization and Portability of a Fusion OpenACC-based FORTRAN HPC Code from NVIDIA to AMD GPUs

Igor Sfiligoi, Emily A. Belli, Jeff Candy, Reuben D. Budiardja

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, Fortran, MPI, nVidia, nVidia A100, OpenACC, Performance

May 21, 2023 by hgpu

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

Matthew Norman, Isaac Lyngaas, Abhishek Bagusetty, Mark Berrill

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Tags: Computer science, Fortran, nVidia, Package, SYCL, Tesla V100

December 19, 2022 by hgpu

Early Application Experiences on a Modern GPU-Accelerated Arm-based HPC Platform

Wael Elwasif, Sergei Bastrakov, Spencer H. Bryngelson, Michael Bussmann, Sunita Chandrasekaran, Florina Ciorba, M. A. Clark, Alexander Debus, William Godoy, Nick Hagerty, Jeff Hammond, David Hardy, J. Austin Harris, Oscar Hernandez, Balint Joo, Sebastian Keller, Paul Kent, Henry Le Berre, Damien Lebrun-Grandie, Elijah MacCarthy, Verónica G. Melesse Vergara, Bronson Messer, Ross Miller, Sarp Oral, Jean-Guillaume Piccinali, Anand Radhakrishnan, Osman Simsek, Filippo Spiga, Klaus Steiniger, Jan Stephan, John E. Stone, Christian Trott, René Widera, Jeffrey Young

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Tags: ARM, Benchmarking, cfd, Computer science, CUDA, Fluid dynamics, Fortran, HPC, MPI, nVidia, nVidia A100, OpenACC, Package

October 2, 2022 by hgpu

SCALSALE: Scalable SALE Benchmark Framework for Supercomputers

Re'em Harel, Matan Rusanovsky, Ron Wagner, Harel Levin, Gal Oren

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Tags: Benchmarking, Computer science, Fortran, HPC, MPI, Package, Performance

September 11, 2022 by hgpu

Automatically Harnessing Sparse Acceleration

Philip Ginsbach, Bruce Collie, Michael F.P. O'Boyle

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Tags: AMD Radeon R7, ATI, Computer science, CUDA, Fortran, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, OpenCL, Performance

January 26, 2020 by hgpu

JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

Samuel S. Schoenholz, Ekin D. Cubuk

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Tags: Biochemistry, Chemistry, Computational Physics, CUDA, Fortran, Machine learning, Materials Science, Molecular dynamics, Neural networks, nVidia, Package, Physics, Python

December 15, 2019 by hgpu

Towards Automatic Transformation of Legacy Scientific Code into OpenCL for Optimal Performance on FPGAs

Wim Vanderbauwhede, Syed Waqar Nabi

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Tags: Compilers, Computer science, Fortran, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenACC, OpenCL, OpenMP, Package

January 6, 2019 by hgpu

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

Reuben D. Budiardja, Christian Y. Cardall

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Tags: cfd, CUDA, Fluid dynamics, Fortran, MPI, nVidia, OpenMP, Package, Physics, Tesla V100

December 23, 2018 by hgpu

Performance Portability Challenges for Fortran Applications

Abigail Hsu, David Neill Asanza, Joseph A. Schoonover, Zach Jibben, Neil N. Carlson, Robert Robey

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Tags: Computer science, CUDA, Finite difference, Fortran, nVidia, OpenMP, Package, performance portability, Tesla P100, Tesla V100

December 2, 2018 by hgpu

New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

Michel Muller, Takayuki Aoki

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Tags: CUDA, Earth and Space Sciences, Fortran, nVidia, OpenACC, Tesla P100, Weather prediction, Weather Prediction Model

March 3, 2018 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

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Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki

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Tags: Earth and Space Sciences, Fortran, nVidia, OpenACC, OpenMP, Package, Tesla K20, Tesla P100, Weather prediction, Weather Prediction Model

October 29, 2017 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

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

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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