Mamba: Portable Array-based Abstractions for Heterogeneous High-Performance Systems

Dykes, Tim; Foyer, Clément; Richardson, Harvey; Svedin, Martin; Podobas, Artur; Jansson, Niclas; Tate, Adrian; McIntosh–Smith, Simon

doi:10.1109/p3hpc54578.2021.00005

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…Neko also provides a device-abstraction layer, where the underlying implementation for the accelerator is hidden to the user. Beneath this layer, Neko uses optimized kernels written in CUDA, HIP, OpenCL for the highest performance, but can be easily extended to other programming models such as Kokkos, SYCL or RAJA (Edwards et al, 2014; Reyes and Lomüller 2016; Hornung and Keasler 2014) without changing the entire codebase, as illustrated with MAMBA (Dykes et al, 2021). Another approach based on Nek5000, NekRS (Fischer et al, 2021), also provides GPU support, but is rewritten in C++ and uses OCCA extensively to generate code for different backends (Medina et al, 2014).…”

Section: Related Workmentioning

confidence: 99%

Large-Scale direct numerical simulations of turbulence using GPUs and modern Fortran

Karp

Massaro

Jansson

et al. 2023

The International Journal of High Performance Computing Applica

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We present our approach to making direct numerical simulations of turbulence with applications in sustainable shipping. We use modern Fortran and the spectral element method to leverage and scale on supercomputers powered by the Nvidia A100 and the recent AMD Instinct MI250X GPUs, while still providing support for user software developed in Fortran. We demonstrate the efficiency of our approach by performing the world’s first direct numerical simulation of the flow around a Flettner rotor at Re = 30,000 and its interaction with a turbulent boundary layer. We present a performance comparison between the AMD Instinct MI250X and Nvidia A100 GPUs for scalable computational fluid dynamics. Our results show that one MI250X offers performance on par with two A100 GPUs and has a similar power efficiency based on readings from on-chip energy sensors.

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Section: Related Workmentioning

confidence: 99%

Large-Scale direct numerical simulations of turbulence using GPUs and modern Fortran

Karp

Massaro

Jansson

et al. 2023

The International Journal of High Performance Computing Applica

Self Cite

View full text Add to dashboard Cite

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Design of Neko—A Scalable High‐Fidelity Simulation Framework With Extensive Accelerator Support

Jansson,

Karp,

Wahlgren

et al. 2024

Concurrency and Computation

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Recent trends and advancements in including more diverse and heterogeneous hardware in High‐Performance Computing (HPC) are challenging scientific software developers in their pursuit of efficient numerical methods with sustained performance across a diverse set of platforms. As a result, researchers are today forced to re‐factor their codes to leverage these powerful new heterogeneous systems. We present our design considerations of Neko—a portable framework for high‐fidelity spectral element flow simulations. Unlike prior works, Neko adopts a modern object‐oriented Fortran 2008 approach, allowing multi‐tier abstractions of the solver stack and facilitating various hardware backends ranging from general‐purpose processors, accelerators down to exotic vector processors and Field‐Programmable Gate Arrays (FPGAs). Focusing on the performance and portability of Neko, we describe the framework's device abstraction layer managing device memory, data transfer and kernel launches from Fortran, allowing for a solver written in a hardware‐neutral yet performant way. Accelerator‐specific optimizations are also discussed, with auto‐tuning of key kernels and various communication strategies using device‐aware MPI. Finally, we present performance measurements on a wide range of computing platforms, including the EuroHPC pre‐exascale system LUMI, where Neko achieves excellent parallel efficiency for a large direct numerical simulation (DNS) of turbulent fluid flow using up to 80% of the entire LUMI supercomputer.

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Mamba: Portable Array-based Abstractions for Heterogeneous High-Performance Systems

Cited by 2 publications

References 23 publications

Large-Scale direct numerical simulations of turbulence using GPUs and modern Fortran

Large-Scale direct numerical simulations of turbulence using GPUs and modern Fortran

Design of Neko—A Scalable High‐Fidelity Simulation Framework With Extensive Accelerator Support

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