Honing and proofing Astrophysical codes on the road to Exascale. Experiences from code modernization on many-core systems

Cielo, Salvatore; Iapichino, Luigi; Baruffa, Fabio; Bugli, Matteo; Federrath, Christoph

doi:10.1016/j.future.2020.05.003

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…As for the MHD simulation, besides technical works describing the code performance [6], the present submission displays its outputs for the first time. Its scientific results will be presented in forthcoming publications.…”

Section: The Largest Turbulence Simulations To Datementioning

confidence: 99%

Visualizing the world's largest turbulence simulation

Cielo¹,

Iapichino²,

Günther³

et al. 2019

Preprint

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In this exploratory submission we present the visualization of the largest interstellar turbulence simulations ever performed, unravelling key astrophysical processes concerning the formation of stars and the relative role of magnetic fields. The simulations, including pure hydrodynamical (HD) and magneto-hydrodynamical (MHD) runs, up to a size of 10048 3 grid elements, were produced on the supercomputers of the Leibniz Supercomputing Centre and visualized using the hybrid parallel (MPI + TBB) ray-tracing engine OSPRay associated with VisIt. Besides revealing features of turbulence with an unprecedented resolution, the visualizations brilliantly showcase the stretching-and-folding mechanisms through which astrophysical processes such as supernova explosions drive turbulence and amplify the magnetic field in the interstellar gas, and how the first structures, the seeds of newborn stars are shaped by this process.

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Section: The Largest Turbulence Simulations To Datementioning

confidence: 99%

Visualizing the world's largest turbulence simulation

Cielo¹,

Iapichino²,

Günther³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Visualizing the world’s largest turbulence simulation

et al. 2021

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Mansard Roofline Model: Reinforcing the Accuracy of the Roofs

Marques

Ilić

Sousa

2021

ACM Trans. Model. Perform. Eval. Comput. Syst.

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Continuous enhancements and diversity in modern multi-core hardware, such as wider and deeper core pipelines and memory subsystems, bring to practice a set of hard-to-solve challenges when modeling their upper-bound capabilities and identifying the main application bottlenecks. Insightful roofline models are widely used for this purpose, but the existing approaches overly abstract the micro-architecture complexity, thus providing unrealistic performance bounds that lead to a misleading characterization of real-world applications. To address this problem, the Mansard Roofline Model (MaRM), proposed in this work, uncovers a minimum set of architectural features that must be considered to provide insightful, but yet accurate and realistic, modeling of performance upper bounds for modern processors. By encapsulating the retirement constraints due to the amount of retirement slots, Reorder-Buffer and Physical Register File sizes, the proposed model accurately models the capabilities of a real platform (average rRMSE of 5.4%) and characterizes 12 application kernels from standard benchmark suites. By following a herein proposed MaRM interpretation methodology and guidelines, speed-ups of up to 5× are obtained when optimizing real-world bioinformatic application, as well as a super-linear speedup of 18.5× when parallelized.

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Honing and proofing Astrophysical codes on the road to Exascale. Experiences from code modernization on many-core systems

Cited by 3 publications

References 25 publications

Visualizing the world's largest turbulence simulation

Visualizing the world's largest turbulence simulation

Visualizing the world’s largest turbulence simulation

Mansard Roofline Model: Reinforcing the Accuracy of the Roofs

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