9th Workshop on Parallel-in-Time Integration

第九届时间集成研讨会密歇根理工大学霍顿，密歇根州2020年6月8日至12日。http：//conferences.math.mtu. edu计算机模型和模拟在工程、生命科学、医学、化学和物理学中的复杂系统研究中发挥着核心作用。利用现代超级计算机来运行模型和模拟，可以在虚拟实验室中进行实验，从而节省时间和资源。虽然下一代超级计算机将包含前所未有数量的处理器，但这不会自动提高运行模拟的速度。需要新的数学算法，可以充分利用这些新系统的处理潜力。本次研讨会的主题是时间并行方法，这是及时和必要的，因为它们通过添加新的可扩展性维度，将现有的计算机模型扩展到这些下一代机器。因此，使用时间并行方法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测）和机器学习。计算和应用数学在这一计划的进步中发挥着基础性作用。并行时间研讨会的主要重点是传播前沿研究，促进并行时间积分方法领域的科学讨论。该研讨会符合国家战略计算计划（NCSI）的目标：“提高建模/仿真技术与数据分析之间的一致性”。 对并行时间积分的需求是由微处理器趋势驱动的，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。因此，随着空间并行技术的饱和，时间方向上的并行化为利用具有数十亿处理器的下一代超级计算机提供了最佳途径。关于并行时间积分器的数学处理，必须使用先进的方法，从偏微分方程理论的功能分析设置，数值离散和积分，迭代方法的收敛性分析，以及新的并行算法的开发和实施。因此，讲习班将汇集这些领域的跨学科专家组。NSF对本次会议的支持将用于吸引年轻研究人员参与这一重要的研究课题。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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.