Scaling implicit parallelism via dynamic control replication

Bauer, Michael; Lee, Wonchan; Slaughter, Elliott; Jia, Zhihao; Renzo, Mario Di; Papadakis, Manolis; Shipman, Galen; McCormick, Patrick; Garland, Michael; Aiken, Alex

doi:10.1145/3437801.3441587

Cited by 9 publications

(2 citation statements)

References 38 publications

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“…The calculations presented in this work are carried out with the described numerical procedure in the Hypersonic Task-based Research (HTR) solver [56][57][58]. The HTR solver leverages the runtime Legion [59][60][61] and the programming language Regent [62] to execute the described calculations on high-performance supercomputers with heterogeneous architectures. Specifically, the supercomputing facility Lassen at the Lawrence Livermore National Laboratory (LLNL) has been utilized in the present work.…”

Section: Computational Setupmentioning

confidence: 99%

Direct numerical simulation of a turbulent methane/air flame impinged by a sub-breakdown electric field

Renzo

Cuenot

2023

Combustion and Flame

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Section: Computational Setupmentioning

confidence: 99%

Direct numerical simulation of a turbulent methane/air flame impinged by a sub-breakdown electric field

Renzo

Cuenot

2023

Combustion and Flame

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“…Table 4 lists the full suite of application codes organized by AD project. The primary DOE platform portability software efforts in ECP are Kokkos, as described in Edwards et al (2014); RAJA, as described in Beckingsale et al (2019); and Legion, as described in Bauer et al (2021). Several projects are also using or experimenting with third-party vendor implementations, including OpenMP, 2 OpenACC, 3 OpenCL, 4 CUDA, 5 HIP, 6 and SYCL.…”

Section: Programming Models Used In Ecpmentioning

confidence: 99%

A survey of software implementations used by application codes in the Exascale Computing Project

Evans

Siegel

Draeger

et al. 2021

The International Journal of High Performance Computing Applica

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The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

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