Stencil computations are a key part of many high-performance computing applications, such as image processing, convolutional neural networks, and finite-difference solvers for partial differential equations. Devito is a framework capable of generating highly optimized code given symbolic equations expressed in Python , specialized in, but not limited to, affine (stencil) codes. The lowering process—from mathematical equations down to C++ code—is performed by the Devito compiler through a series of intermediate representations. Several performance optimizations are introduced, including advanced common sub-expressions elimination, tiling, and parallelization. Some of these are obtained through well-established stencil optimizers, integrated in the backend of the Devito compiler. The architecture of the Devito compiler, as well as the performance optimizations that are applied when generating code, are presented. The effectiveness of such performance optimizations is demonstrated using operators drawn from seismic imaging applications.

Abstract. We introduce Devito, a new domain-specific language for implementing high-performance finite-difference partial differential equation solvers. The motivating application is exploration seismology for which methods such as full-waveform inversion and reverse-time migration are used to invert terabytes of seismic data to create images of the Earth's subsurface. Even using modern supercomputers, it can take weeks to process a single seismic survey and create a useful subsurface image. The computational cost is dominated by the numerical solution of wave equations and their corresponding adjoints. Therefore, a great deal of effort is invested in aggressively optimizing the performance of these wave-equation propagators for different computer architectures. Additionally, the actual set of partial differential equations being solved and their numerical discretization is under constant innovation as increasingly realistic representations of the physics are developed, further ratcheting up the cost of practical solvers. By embedding a domain-specific language within Python and making heavy use of SymPy, a symbolic mathematics library, we make it possible to develop finite-difference simulators quickly using a syntax that strongly resembles the mathematics. The Devito compiler reads this code and applies a wide range of analysis to generate highly optimized and parallel code. This approach can reduce the development time of a verified and optimized solver from months to days.

The academic debate on flood risk governance is paying increased attention to the shifting position of homeowners. Homeowners are increasingly expected to adapt their homes to protect against possible floods. Although an overall agreement seems to exist on the involvement of homeowners in flood risk governance, the academic literature is dispersed in its argumentation on why homeowners should be involved. Therefore, this article provides a coherent overview of the transition from flood protection to flood risk management, and subsequently of the arguments that unfold regarding the shifting position of homeowners within this debate. This overview, based on a systematic review of the academic literature, helps to shed light on the changing role of homeowners in flood risk governance and contributes to categorizing the arguments used in current academic reasoning on homeowner involvement in flood risk governance. We use a conceptual distinction between macro‐level and micro‐level arguments, and between individual and collective efforts to structure our results. This conceptual overview illustrates the potential gap in convincing homeowners of the urgency to take action, because the connection between the macro‐level arguments (i.e., climate change and responsibility) and the micro‐level arguments (i.e., minimizing flood damage on privately owned properties) is generally not made. We, therefore, suggest that a stronger coherence in the argumentation would contribute to increase homeowner awareness of their changing responsibilities, which might bring about a future shift toward a new phase in flood risk governance, in which the responsibilities of homeowners are more explicitly acknowledged and integrated into climate adaptation strategies. This article is categorized under: Engineering Water > Planning Water Human Water > Water Governance

Many urban residences are insufficiently prepared for fluvial, pluvial or coastal floods, owing to a lack of accurate information on flood risk. This article analyzes how risk communication can improve disaster risk reduction by overcoming the expert-layperson gap. Building on interviews in three cities in the Netherlands, it applies Q methodology to identify four perspectives on flood risk communication. To promote greater private residential involvement in flood risk adaptation, communication should address all four rationalities.

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