9th Workshop on Parallel-in-Time Integration

第九期并行集成研讨会密歇根理工大学霍顿，密歇根6月8-12,2020.http://conferences.math.mtu.eduComputer模型和模拟在工程、生命科学、医学、化学和物理的复杂系统研究中发挥着核心作用。利用现代超级计算机运行模型和模拟，允许在虚拟实验室中进行实验，从而节省了时间和资源。尽管下一代超级计算机将包含前所未有的处理器数量，但这不会自动提高运行模拟的速度。需要新的数学算法来充分利用这些新系统的处理潜力。本研讨会的主题-时间并行方法是及时和必要的，因为它们通过增加新的可伸缩性维度将现有的计算机模型扩展到这些下一代机器。因此，时间并行方法的使用将在许多重要领域提供显著更快的模拟，例如生物医学应用(例如，心脏建模)、计算流体动力学(例如，空气动力学和天气预报)和机器学习。计算和应用数学在这一预期的进步中起着基础性的作用。时间并行讲习班的主要重点是传播前沿研究，促进关于并行时间积分方法领域的科学讨论。该研讨会与国家战略计算倡议(NCSI)的目标一致：“提高建模/模拟技术与数据分析之间的一致性”。对并行时间整合的需求正受到微处理器趋势的推动，未来计算模拟的加速将通过使用越来越多的内核来实现，而不是通过更快的时钟速度来实现。因此，随着空间并行技术饱和，时间方向的并行为利用拥有数十亿处理器的下一代超级计算机提供了最好的途径。关于并行时间积分器的数学处理，必须使用泛函分析环境下的偏微分方程组理论、数值离散和积分、迭代方法的收敛分析以及新的并行算法的开发和实现的先进方法。因此，研讨会将汇聚一个涵盖这些领域的跨学科专家组。NSF对这次会议的支持将被用来吸引初级研究人员参与这一重要的研究主题。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

9th Workshop on Parallel-in-Time IntegrationMichigan Technological University Houghton, Michigan June 8-12,2020.http://conferences.math.mtu.eduComputer models and simulations play a central role in the study of complex systems in engineering, life sciences, medicine, chemistry, and physics. Utilizing modern supercomputers to run models and simulations allows for experimentation in virtual laboratories, thus saving both time and resources. Although the next generation of supercomputers will contain an unprecedented number of processors, this will not automatically increase the speed of running simulations. New mathematical algorithms are needed that can fully harness the processing potential of these new systems. Parallel-in-time methods, the subject of this workshop, are timely and necessary, as they extend existing computer models to these next generation machines by adding a new dimension of scalability. Thus, the use of parallel-in-time methods will provide dramatically faster simulations in many important areas, such as biomedical applications (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning. Computational and applied mathematics plays a foundational role in this projected advancement. The primary focus of the parallel-in-time workshop is to disseminate cutting-edge research and facilitate scientific discussions on the field of parallel time integration methods. This workshop aligns with the National Strategic Computing Initiative (NCSI) objective: 'increase coherence between technology for modeling/simulation and data analytics'. The need for parallel time integration is being driven by microprocessor trends, where future speedups for computational simulations will come through using increasing numbers of cores and not through faster clock speeds. Thus as spatial parallelism techniques saturate, parallelization in the time direction offers the best avenue for leveraging next generation supercomputers with billions of processors. Regarding the mathematical treatment of parallel time integrators, one must use advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Thus, the workshop will bring together an interdisciplinary group of experts spanning these areas. NSF support for this conference will be used to engage junior researchers in this important research topic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.