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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

Performance portability evaluation of blocked stencil computations on GPUs

Oscar Antepara, Hans Johansen, Samuel Williams, Tuowen Zhao, Samantha Hirsch, Priya Goyal, Mary Hall

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Tags: AMD Radeon Instinct MI250X, ATI, Code generation, Computer science, CUDA, HIP, nVidia, nVidia A100, Package, performance portability, Stencil computation, SYCL

October 29, 2023 by hgpu

ProtoX: A First Look

Het Mankad, Sanil Rao, Brian Van Straalen, Phillip Colella, Franz Franchetti

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Tags: Code generation, Computer science, Differential equations, Laplace and Poisson equation, Mathematical Software, Partial differential equations, PDEs, Poisson equation, Stencil computation

July 24, 2023 by hgpu

EPSILOD: efficient parallel skeleton for generic iterative stencil computations in distributed GPUs

Manuel de Castro, Inmaculada Santamaria-Valenzuela, Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: AMD FirePro W9100, ATI, Computer science, Heterogeneous systems, Numerical simulation, nVidia, OpenCL, Package, Stencil computation, Tesla V100

February 12, 2023 by hgpu

Persistent Kernels for Iterative Memory-bound GPU Applications

Lingqi Zhang, Mohamed Wahib, Peng Chen, Jintao Meng, Xiao Wang, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla A100, Tesla V100

April 10, 2022 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

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Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

Efficient Nearest-Neighbor Data Sharing in GPUs

Negin Nematollahi, Mohammad Sadrosadati, Hajar Falahati, Marzieh Barkhordar, Mario Paulo Drumond, Hamid Sarbazi-Azad, Babak Falsafi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 980, Stencil computation

January 10, 2021 by hgpu

Accelerating High-Order Stencils on GPUs

Ryuichi Sai, John Mellor-Crummey, Xiaozhu Meng, Mauricio Araya-Polo, Jie Meng

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Tags: Computer science, HPC, nVidia, nVidia Quadro NVS 510, Package, Performance, Stencil computation, Tesla P100, Tesla V100

September 13, 2020 by hgpu

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

Hamid Reza Zohouri, Artur Podobas, Satoshi Matsuoka

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Tags: Computer science, FPGA, OpenCL, Stencil computation

February 23, 2020 by hgpu

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

Peng Chen, Mohamed Wahib, Shinichiro Takizawa, Ryousei Takano, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla P100, Tesla V100

July 21, 2019 by hgpu

On Optimizing Complex Stencils on GPUs

Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, Stencil computation, Tesla P100

April 20, 2019 by hgpu

Delivering Performance-Portable Stencil Computations on CPUs and GPUs Using Bricks

Tuowen Zhao, Samuel Williams, Mary Hall, Hans Johansen

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, performance portability, Stencil computation, Tesla P100

December 16, 2018 by hgpu

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high performance computing on graphics processing units: hgpu.org

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

Performance portability evaluation of blocked stencil computations on GPUs

ProtoX: A First Look

EPSILOD: efficient parallel skeleton for generic iterative stencil computations in distributed GPUs

Persistent Kernels for Iterative Memory-bound GPU Applications

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Efficient Nearest-Neighbor Data Sharing in GPUs

Accelerating High-Order Stencils on GPUs

High-Performance High-Order Stencil Computation on FPGAs Using OpenCL

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

On Optimizing Complex Stencils on GPUs

Delivering Performance-Portable Stencil Computations on CPUs and GPUs Using Bricks

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