high performance computing on graphics processing units: hgpu.org

Ka Hei Martin Kwok, Matti Kortelainen, Giuseppe Cerati, Alexei Strelchenko, Oliver Gutsche, Allison Reinsvold Hall, Steve Lantz, Michael Reid, Daniel Riley, Sophie Berkman, Seyong Lee, Hammad Ather, Boyana Norris, Cong Wang

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Tags: AMD Radeon Instinct MI100, ATI, HEP, Intel, Intel Arc A770, nVidia, nVidia A100, nVidia V100, OpenMP, performance portability, Physics, SYCL

January 28, 2024 by hgpu

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Aristotle Martin, Geng Liu, William Ladd, Seyong Lee, John Gounley, Jeffrey Vetter, Saumil Patel, Silvio Rizzi, Victor Mateevitsi, Joseph Insley, Amanda Randles

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, CUDA, Fluid dynamics, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia V100, performance portability, SYCL

December 31, 2023 by hgpu

Principles for Automated and Reproducible Benchmarking

Tuomas Koskela, Ilektra Christidi, Mosè Giordano, Emily Dubrovska, Jamie Quinn, Christopher Maynard, Dave Case, Kaan Olgu, Tom Deakin

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Tags: Benchmarking, Computer science, HPC, nVidia, oneAPI, Package, performance portability

December 18, 2023 by hgpu

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

Enrique G. Paredes, Linus Groner, Stefano Ubbiali, Hannes Vogt, Alberto Madonna, Kean Mariotti, Felipe Cruz, Lucas Benedicic, Mauro Bianco, Joost VandeVondele, Thomas C. Schulthess

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Tags: CUDA, Earth and Space Sciences, nVidia, Package, performance portability, Python, Stencil computation, Tesla P100, Weather prediction

November 27, 2023 by hgpu

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

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high performance computing on graphics processing units: hgpu.org

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Automatic Code Rewriting for Performance Portability

Experiences with implementing Kokkos’ SYCL backend

Retargeting and Respecializing GPU Workloads for Performance Portability

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

An Evaluative Comparison of Performance Portability across GPU Programming Models

pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Principles for Automated and Reproducible Benchmarking

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

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