Collaborative Research: Petascale Simulation of Viral Infection Propogation through Air Travel

航空旅行已被认为是流感等感染传播的主要因素，这促使人们呼吁限制航空旅行，以防止疾病爆发的传播。然而，这种限制带来了相当大的经济和人力成本。因此，有必要评估航空旅行对病毒性疾病传播的影响程度，并确定可以在不严重干扰航空旅行的情况下减轻其传播的政策选择。计算机模拟在评估可行的政策选择和探索政策制定者决策的潜在后果方面发挥着至关重要的作用。 VIPRA 项目的目标是使用 Blue Waters 领先计算系统创建大规模并行模拟基础设施，为处理航空旅行中病毒感染传播的决策者提供有用的见解。 该基础设施将有助于制定新政策，减少大流行的可能性，为 NSF 促进我们国家的健康、繁荣和福祉的使命做出贡献。 VIPRA 项目使用人类运动的精细模型，该模型可以捕获详细的动态，因此可以评估程序中细微变化的影响，这些变化有可能大幅降低流行病通过航空旅行传播的可能性。这种精细尺度的方法存在计算成本高的瓶颈。在 Blue Waters 的初步工作中，与埃博拉病毒病在飞机上传播相关的主要计算部分所需的时间已从每次运行大约 70,000 个核心的几个小时减少到大约 20 分钟。这些优化使得在紧急情况发生之前分析预期政策变得容易。然而，在决策会议过程中，潜在新政策的结果需要在几分钟内得出。此外，在机场中出现的更复杂的情况下，空气传播的病毒性疾病将需要更大的计算量。这可以使用 Blue Waters 上的 GPU 并进一步将计算扩展到更大的并行度来处理。 Blue Waters 的这项分配将支持部署优化的决策支持系统，该系统可以在新紧急情况的时间限制下分析政策或程序选项。

Air travel has been identified as a leading factor in the spread of infections, such as influenza, and this has motivated calls for limitations on air travel in order to prevent the spread of disease outbreak. However, such limitations carry considerable economic and human costs. Consequently, it is necessary to evaluate the extent of impact of air travel on spread of viral diseases and to also identify policy options that can mitigate its spread without major disruption to air travel. Computer simulations play a crucial role in evaluating viable policy options and exploring potential consequences of decisions taken by policy makers. The goal of Project VIPRA is to use the Blue Waters leadership computing system to create a massively parallel simulation infrastructure that will provide useful insight to decision makers dealing with viral infection propagation through air travel. This infrastructure will enable formulation of new policies that will reduce the likelihood of a pandemic, contributing to NSF's mission to advance the health, prosperity and welfare of our nation.Project VIPRA uses a fine-scale model for human movement, which can capture detailed dynamics, and so can evaluate the impact of subtle changes in procedures that have the potential to bring a substantial reduction in the likelihood of an epidemic spreading through air travel. This fine-scale approach comes with the bottleneck of high computational cost. In preliminary work on Blue Waters, the time required for the primary component of the computation, related to spread of Ebola Virus Disease in an airplane, has been reduced from several hours to around 20 minutes per run on approximately 70,000 cores. These optimizations make it easy to analyze anticipated policies ahead of an emergency. However, in the course of a decision meeting, results for potential new policies need to be produced within a couple of minutes. In addition, air-borne viral diseases, in the more complex situations seen in airports, will require even greater computational effort. This can be handled using GPUs on Blue Waters and by further scaling the computation to greater parallelism. This Blue Waters allocation will enable deployment of an optimized decision support system that can analyze policy or procedural options in the time constraints of a new emergency.