Game-Changing Time Integration of Complex Systems for the Exaflop Era

Exaflop 时代复杂系统的改变游戏规则的时间集成

• 批准号: 228090-2013
• 负责人: Spiteri, Raymond
• 金额: $ 2.19万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683472
• 关键词: Game; Changing; Time; Integration; Complex

It is an exciting time to be a computational scientist. By 2018, some predict we will be in the exaflop era, in which supercomputers will be some 20 times more powerful than the human brain. The enormity of these figures is rivalled only by that of the emergent opportunities for applications of this computing power. Exascale computing would allow us to tackle grand challenge problems in virtual medicine, climate change, renewable energy, advanced materials, resource recovery, and national security. These problems offer a fundamental connection between extreme computing, industrial and economic growth, and societal imperatives.The broad objectives of this research are to develop effective numerical methods and software for the simulation of complex systems that are amenable to current trends in computing hardware, especially those that are envisaged to support exascale computing. The mathematical models for the systems we study are based on evolutionary differential equations. These systems typically have multiple interacting time scales, and accordingly no single time-integration method has the characteristics to handle them all in an effective manner. The specific approach we employ is based on intelligent, fine-scale partitioning strategies combined with the design of optimized time-integration methods.Our present focus is on applying this approach to simulate the electrical activity in the heart. We have proposed novel time-integration methods for such simulations and have already demonstrated performance improvements of up to factors of 300 over current state-of-the-art methods. In the longer term, we plan to tackle whole heart simulations, in which models of electrical activity are further augmented to take into account tissue elasticity and blood flow. The performance gains in heart simulation will bring us closer to simulations that are fast enough to benefit clinical training and practice as well as personalized medicine. This research aims to provide the computational breakthroughs that can ultimately lead to an improvement in the quality of life of millions of people in Canada and around the world who are affected by heart disease.

成为一名计算科学家是一个激动人心的时刻。到2018年，有些人预测我们将处于Exaflop时代，其中超级计算机将比人脑强大20倍。这些数字的巨大性仅与该计算能力应用的新兴机会相匹配。 Exascale计算将使我们能够解决虚拟医学，气候变化，可再生能源，高级材料，资源回收和国家安全方面的挑战问题。这些问题提供了极端计算，工业和经济增长与社会需求之间的基本联系。这项研究的广泛目标是开发有效的数值方法和软件，以模拟复杂系统的模拟，这与当前计算硬件的趋势相吻合，尤其是那些设想支持Exascale Computing的问题。我们研究的系统的数学模型基于进化微分方程。这些系统通常具有多个相互作用的时间尺度，因此，没有单个时间整合方法具有有效方式处理它们的特征。我们采用的具体方法是基于智能，细度的分区策略，结合了优化的时间整合方法的设计。我们当前的重点是应用这种方法来模拟心脏中的电活动。我们已经提出了用于此类模拟的新型时间整合方法，并且已经证明了与当前最新方法相比300个因素的性能改善。 从长远来看，我们计划解决全心模拟，其中进一步增强电活动模型以考虑组织弹性和血液的流动。 心脏模拟中的性能提高将使我们更接近仿真，这些模拟足够快，可以使临床培训和实践以及个性化医学受益。这项研究旨在提供计算突破，最终可以改善加拿大和世界各地受心脏病影响的数百万人的生活质量。