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

航空旅行已被确定为流感等传染病传播的主要因素，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，并确定能够在不对航空旅行造成重大干扰的情况下减缓病毒性疾病传播的政策选择。计算机模拟在评估可行的政策选择和探索决策者所作决定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沃茨领导力计算系统创建大规模并行模拟基础设施，为决策者处理通过航空旅行传播的病毒感染提供有用的见解。 这一基础设施将有助于制定新的政策，这将减少大流行的可能性，有助于NSF的使命，以促进我们国家的健康，繁荣和福利。VIPRA项目使用精细规模的人类运动模型，可以捕捉详细的动态，因此可以评估程序中细微变化的影响，这些变化有可能大大降低流行病的可能性通过空中旅行传播这种精细尺度的方法带来了高计算成本的瓶颈。在Blue沃茨的初步工作中，与飞机上埃博拉病毒疾病传播有关的计算的主要组成部分所需的时间已经从每次运行约7万个核心的几个小时减少到约20分钟。这些优化使得在紧急情况发生之前分析预期的政策变得容易。然而，在决策会议的过程中，需要在几分钟内产生潜在新政策的结果。此外，空气传播的病毒性疾病，在机场看到的更复杂的情况下，将需要更大的计算工作。这可以通过在Blue沃茨上使用GPU来处理，并通过进一步扩展计算以实现更大的并行性。这一蓝色沃茨分配将能够部署一个优化的决策支持系统，该系统可以在新的紧急情况的时间限制内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.