1st CEEC Community Workshop: Energy-Efficient, Fault Resilient, and Scalable Solvers for CFD Codes

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Join us for our first annual community workshop! The energy consumption constraint for large-scale computing encourages scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. The main aim is to make the computations energy-efficient (aka sustainable) and robust numerically but also in terms of fault tolerance. On the level of algorithmic solutions, we propose to utilize all provided resources wisely by exhibiting algorithms to computation overlapping but even more communication overlapping strategies. We also promote mixed-precision strategies with the aid of computer arithmetic tools like VerifiCarlo and its variable precision backend. Hence, before lowering precision, one must ensure that the simulation is numerically correct, e.g. by relying on alternative floating-point models/ rounding to pinpoint numerical bugs and to estimate the accuracy. We also work on fault tolerant and resilient algorithms, adaptivity and meshing/ mesh refinement that adapt to the heterogeneous nature of current machines. Another issue discussed in the workshop is the adaptation of adjoint-based topology optimization methods to spectral-element CFD codes. Therefore, in this workshop, we will share our approaches, lessons learnt with preliminary results, and outline perspectives for the upcoming three years of the project.

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Summer Round-Up

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It’s been a while since our last update, and we’re still in the early days of our work. That said, we’ve been travelling to introduce ourselves and present some of the work we’ll be building on during our 4 project years. Maybe you’ve seen us? This summer we had various presentations both at ISC High-Performance and at the Platform for Advanced Scientific Computing (PASC) conference

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VPREC to analyze the precision appetites and numerical abnormalities of several proxy applications

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The third in a series of presentations from Roman Iakymchuk on work using tools to investigate mixed precision possibilities. He and his co-author Pablo de Oliveira Castro introduce an approach to address the issue of sustainable computations with computer arithmetic tools. They use the variable precision backend (VPREC) to identify parts of code that can benefit from smaller floating-point formats and show preliminary results on several proxy applications.

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MS4F – Cross-Cutting Aspects of Exploiting Exascale Platforms for High-Fidelity CFD in Turbulence Research

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This minisymposium was chaired by a CEEC consortium member and contained the presentation of another CEEC consortium member. The arrival of exascale computing has opened up unprecedented simulation capabilities for Computational Fluid Dynamics (CFD) applications. While offering high theoretical peak performance and high memory bandwidth, efficiently exploiting these systems necessitates complex programming models and significant programming investments .

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Sustainable and Reliable Computing with Tools: Analyzing Precision Appetites of CFD Applications with VerifiCarlo

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Energy consumption constraints for large-scale computing encourage scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. I will introduce an approach to address the issue of sustainable, but still reliable, computations from the perspective of computer arithmetic tools. We employ VerifiCarlo and its variable precision backend to identify the parts of the code that benefit from smaller floating-point formats. Finally, we show preliminary results on proxies of CFD applications.

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Reliable and sustainable computations: An application-driven approach

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In this talk, Roman Iakymchuk presents his work on accuracy and reproducibility assuring strategies for parallel iterative solvers that may not hold due to the non-associativity of floating-point operations. These strategies primarily rely on guarding every bit of result until final rounding, hence they can be costly. The energy consumption constraint for large-scale computing encourages scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. The main aim is to make the computing cost sustainable and apply the lagom principle (''not too much, not too little, the right amount"), especially when it comes to working/ storage precision. Thus, he will introduce an approach to address the issue of sustainable, but still reliable, computations from the perspective of computer arithmetic tools. Before lowering precision, one must ensure that the simulation is numerically correct, e.g. by relying on alternative floating-point models/ rounding to pinpoint numerical bugs and to estimate the accuracy. We employ VerifiCarlo and its variable precision backend to identify the parts of the code that benefit from smaller floating-point formats. Finally, we show preliminary results on proxy applications.

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