Stella

Gysi, Tobias; Osuna, Carlos; Fuhrer, Oliver; Bianco, Mauro; Schulthess, T. C.

doi:10.1145/2807591.2807627

Cited by 79 publications

(23 citation statements)

References 18 publications

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“…Choosing an alternative route, the dynamical core of the COSMO model has been rewritten using the GridTools DSL (Gysi et al 2015;Fuhrer et al 2014). GridTools is a domain-specific language that eases the burden of the application developer by separating the architecture dependent implementation strategy from the user code.…”

Section: Strategies Toward Kilometer-scale Resolutionmentioning

confidence: 99%

Kilometer-Scale Climate Models: Prospects and Challenges

Schär

Fuhrer

Arteaga

et al. 2020

Bulletin of the American Meteorological Society

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158

125

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Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limitedarea numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.

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Section: Strategies Toward Kilometer-scale Resolutionmentioning

confidence: 99%

Kilometer-Scale Climate Models: Prospects and Challenges

Schär

Fuhrer

Arteaga

et al. 2020

Bulletin of the American Meteorological Society

Self Cite

158

125

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“…As demonstrated in [24,22,23,25], the code achieves excellent performance on CPUs, GPUs and Xeon Phi processors. Similar techniques for structured grids have been used to develop the C++ based STELLA grid library for the COSMO numerical weather forecast model [26]. DSLs for highly efficient stencil computations on GPUs have also been described in [27,28].…”

Section: Introductionmentioning

confidence: 99%

A domain specific language for performance portable molecular dynamics algorithms

Saunders

Grant

Müller

2018

Computer Physics Communications

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Developers of Molecular Dynamics (MD) codes face significant challenges when adapting existing simulation packages to new hardware. In a continuously diversifying hardware landscape it becomes increasingly difficult for scientists to be experts both in their own domain (physics/chemistry/biology) and specialists in the low level parallelisation and optimisation of their codes. To address this challenge, we describe a "Separation of Concerns" approach for the development of parallel and optimised MD codes: the science specialist writes code at a high abstraction level in a domain specific language (DSL), which is then translated into efficient computer code by a scientific programmer. In a related context, an abstraction for the solution of partial differential equations with grid based methods has recently been implemented in the (Py)OP2 library. Inspired by this approach, we develop a Python code generation system for molecular dynamics simulations on different parallel architectures, including massively parallel distributed memory systems and GPUs. We demonstrate the efficiency of the auto-generated code by studying its performance and scalability on different hardware and compare it to other state-of-the-art simulation packages. With growing data volumes the extraction of physically meaningful information from the simulation becomes increasingly challenging and requires equally efficient implementations. A particular advantage of our approach is the easy expression of such analysis algorithms. We consider two popular methods for deducing the crystalline structure of a material from the local environment of each atom, show how they can be expressed in our abstraction and implement them in the code generation framework.

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“…There also exists several high-level DSL-type frameworks used in weather modeling applications such as STELLA [59] (and its successor GridTools) and PSyclone [60]. While the parallel motif targeted by these frameworks are the same as OPS (i.e.…”

Section: Related Workmentioning

confidence: 99%

Large-scale performance of a DSL-based multi-block structured-mesh application for Direct Numerical Simulation

Mudalige

Reguly

Jammy

et al. 2019

Journal of Parallel and Distributed Computing

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SBLI (Shock-wave/Boundary-layer Interaction) is a large-scale Computational Fluid Dynamics(CFD) application, developed over 20 years at the University of Southampton and extensively used within the UK Turbulence Consortium. It is capable of performing Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) of shock-wave/boundarylayer interaction problems over highly detailed multi-block structured mesh geometries. SBLI presents major challenges in data organization and movement that need to be overcome for continued high performance on emerging massively parallel hardware platforms. In this paper we present research in achieving this goal through the OPS embedded domainspecific language. OPS targets the domain of multi-block structured mesh applications. It provides an API embedded in C/C++ and Fortran and makes use of automatic code generation and compilation to produce executables capable of running on a range of parallel hardware systems. The core functionality of SBLI is captured using a new framework called OpenSBLI which enables a developer to declare the partial differential equations using Einstein notation and then automatically carryout discretization and generation of OPS (C/C++) API code. OPS is then used to automatically generate a wide range of parallel implementations. Using this multi-layered abstractions approach we demonstrate how new opportunities for further optimizations can be gained, such as fine-tuning the computation intensity and reducing data movement and apply them automatically. Performance results demonstrate there is no performance loss due to the high-level development strategy with OPS and OpenSBLI, with performance matching or exceeding the hand-tuned original code on all CPU nodes tested. The data movement optimizations provide over 3× speedups on CPU nodes, while GPUs provide 5× speedups over the best performing CPU node. The OPS generated parallel code also demonstrates excellent scalability on nearly 100K cores on a Cray XC30 (ARCHER at EPCC) and on over 4K GPUs on a CrayXK7 (Titan at ORNL).

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Stella

Cited by 79 publications

References 18 publications

Kilometer-Scale Climate Models: Prospects and Challenges

Kilometer-Scale Climate Models: Prospects and Challenges

A domain specific language for performance portable molecular dynamics algorithms

Large-scale performance of a DSL-based multi-block structured-mesh application for Direct Numerical Simulation

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