high performance computing on graphics processing units: hgpu.org

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Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Gabin Schieffer, Ruimin Shi, Stefano Markidis, Andreas Herten, Jennifer Faj, Ivy Peng

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Tags: AMD, AMD Radeon Instinct MI250X, ATI, Computer science, HIP, Machine learning, Memory, Performance

October 6, 2024 by hgpu

OpenACC offloading of the MFC compressible multiphase flow solver on AMD and NVIDIA GPUs

Benjamin Wilfong, Anand Radhakrishnan, Henry A. Le Berre, Steve Abbott, Reuben D. Budiardja, Spencer H. Bryngelson

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, MPI, nVidia, OpenACC, Package, Tesla V100

September 29, 2024 by hgpu

Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

Daniele De Sensi, Lorenzo Pichetti, Flavio Vella, Tiziano De Matteis, Zebin Ren, Luigi Fusco, Matteo Turisini, Daniele Cesarini, Kurt Lust, Animesh Trivedi, Duncan Roweth, Filippo Spiga, Salvatore Di Girolamo, Torsten Hoefler

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, Computer science, CUDA, HPC, MPI, nVidia, nVidia A100, nVidia H100, Performance

September 1, 2024 by hgpu

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

Aaron Jarmusch, Felipe Cabarcas, Swaroop Pophale, Andrew Kallai, Johannes Doerfert, Luke Peyralans, Seyong Lee, Joel Denny, Sunita Chandrasekaran

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Tags: AMD Radeon Instinct MI210, AMD Radeon Instinct MI250X, ATI, Compilers, Computer science, Fortran, Heterogeneous systems, HPC, nVidia, nVidia H100, OpenMP

August 25, 2024 by hgpu

HiCCL: A Hierarchical Collective Communication Library

Mert Hidayetoglu, Simon Garcia de Gonzalo, Elliott Slaughter, Pinku Surana, Wen-mei Hwu, William Gropp, Alex Aiken

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, HIP, nVidia, nVidia A100, Package, Performance, SYCL

August 18, 2024 by hgpu

Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs

Milo Lurati, Stijn Heldens, Alessio Sclocco, Ben van Werkhoven

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Pro W6600, ATI, Computer science, CUDA, HIP, nVidia, nVidia A100, nVidia RTX A4000, Package, Performance, Python

July 28, 2024 by hgpu

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Johannes Pekkilä, Oskar Lappi, Fredrik Robertsén, Maarit J. Korpi-Lagg

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Energy-efficient computing, HIP, nVidia, nVidia A100, nVidia V100, Package, Performance, PyTorch, Stencil computation

June 16, 2024 by hgpu

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Martin Karp

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, FPGA, Heterogeneous systems, Numerical simulation, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, Spectral elements, Thesis

May 12, 2024 by hgpu

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Andrey Alekseenko, Szilárd Páll, Erik Lindahl

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Tags: AMD Radeon Instinct MI250X, ATI, Biomolecules, Computational Physics, Computer science, Heterogeneous systems, Molecular dynamics, Molecular simulation, Performance, SYCL

May 5, 2024 by hgpu

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

Francesco Salvadore, Giacomo Rossi, Srikanth Sathyanarayana, Matteo Bernardini

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Tags: AMD Radeon Instinct MI250X, ATI, Benchmarking, cfd, Compression, Fluid dynamics, Intel, Intel Data Center GPU Max 1550, nVidia, nVidia A100, OpenMP

April 14, 2024 by hgpu

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

John Tramm, Paul Romano, Patrick Shriwise, Amanda Lund, Johannes Doerfert, Patrick Steinbrecher, Andrew Siegel, Gavin Ridley

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Intel, Intel Data Center GPU Max 1550, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenMP, Package, performance portability

March 24, 2024 by hgpu

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

Xinyi Li, Ang Li, Bo Fang, Katarzyna Swirydowicz, Ignacio Laguna, Ganesh Gopalakrishnan

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, Hardware Architecture, HPC, Matrix multiplication, nVidia, nVidia A100, nVidia H100, nVidia V100, PTX

March 10, 2024 by hgpu

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high performance computing on graphics processing units: hgpu.org

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

OpenACC offloading of the MFC compressible multiphase flow solver on AMD and NVIDIA GPUs

Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

HiCCL: A Hierarchical Collective Communication Library

Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

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

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

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