Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Towards CFD 2030

International audienceUnstructured grid adaptation is a powerful tool to control Computational Fluid Dynamics (CFD) discretization error. It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provide a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The study authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity will continue to be significant bottlenecks in the CFD workflow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to di↵use grid adaptation technology into production CFD work flows

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest

Scalable Multithreaded Algorithms for Mutable Irregular Data with Application to Anisotropic Mesh Adaptivity

Anisotropic mesh adaptation is a powerful way to directly minimise the computational cost of mesh based simulation. It is particularly important for multi-scale problems where the required number of floating-point operations can be reduced by orders of magnitude relative to more traditional static mesh approaches. Increasingly, finite element/volume codes are being optimised for modern multicore architectures. Inter-node parallelism for mesh adaptivity has been successfully implemented by a number of groups using domain decomposition methods. However, thread-level parallelism using programming models such as OpenMP is significantly more challenging because the underlying data structures are extensively modified during mesh adaptation and a greater degree of parallelism must be realised while keeping the code race-free. In this thesis we describe a new thread-parallel implementation of four anisotropic mesh adaptation algorithms, namely edge coarsening, element refinement, edge swapping and vertex smoothing. For each of the mesh optimisation phases we describe how safe parallel execution is guaranteed by processing workitems in batches of independent sets and using a deferred-operations strategy to update the mesh data structures in parallel without data contention. Scalable execution is further assisted by creating worklists using atomic operations, which provides a synchronisation-free alternative to reduction-based worklist algorithms. Additionally, we compare graph colouring methods for the creation of independent sets and present an improved version which can run up to 50% faster than existing techniques. Finally, we describe some early work on an interrupt-driven work-sharing for-loop scheduler which is shown to perform better than existing work-stealing schedulers. Combining all aforementioned novel techniques, which are generally applicable to other unordered irregular problems, we show that despite the complex nature of mesh adaptation and inherent load imbalances, we achieve a parallel efficiency of 60% on an 8-core Intel(R) Xeon(R) Sandy Bridge and 40% using 16 cores on a dual-socket Intel(R) Xeon(R) Sandy Bridge ccNUMA system.Open Acces

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Anales del XIII Congreso Argentino de Ciencias de la Computación (CACIC)

Contenido: Arquitecturas de computadoras Sistemas embebidos Arquitecturas orientadas a servicios (SOA) Redes de comunicaciones Redes heterogéneas Redes de Avanzada Redes inalámbricas Redes móviles Redes activas Administración y monitoreo de redes y servicios Calidad de Servicio (QoS, SLAs) Seguridad informática y autenticación, privacidad Infraestructura para firma digital y certificados digitales Análisis y detección de vulnerabilidades Sistemas operativos Sistemas P2P Middleware Infraestructura para grid Servicios de integración (Web Services o .Net)Red de Universidades con Carreras en Informática (RedUNCI