GPU-based Real-time Contact Tracing at Scale.
GPU-based Real-time Contact Tracing at Scale.
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DOI：
10.1145/3474717.3483627
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发表时间：
2021-11
期刊：
影响因子：
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通讯作者：
Wang F
中科院分区：
文献类型：
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作者：
Teng D;Nehe A;Emanuel P;Baig F;Kong J;Wang F
接触者追踪在控制COVID-19传播方面的重要性日益凸显。然而，频繁采样的跟踪数据量巨大，给实时处理带来了重大挑战。在本文中，我们提出了一种基于gpu的实时接触追踪系统，该系统基于具有时间约束的空间接近查询。我们在GPU上使用自适应分区模式提供移动对象的动态索引，开销极低。我们的系统优化了接触对的检索，以满足接触跟踪场景和GPU中心并行性的要求。我们提出了一种有效的接触评估机制，只保留空间和时间上有效的接触。我们的实验表明，该系统可以实现亚秒级响应，用于数千万人的大规模接触追踪，性能比基于CPU的方法提高了两个数量级。
Contact tracing is gaining its importance in controlling the spread of COVID-19. However, the enormous volume of the frequently sampled tracing data brings major challenges for real-time processing. In this paper, we propose a GPU-based real-time contact tracing system based on spatial proximity queries with temporal constraints using location data. We provide dynamic indexing of moving objects using an adaptive partitioning schema on GPU with extremely low overhead. Our system optimizes the retrieval of contacted pairs to match both the requirements of contact tracing scenarios and GPU centered parallelism. We propose an efficient contacts evaluation mechanism to keep only the spatially and temporally valid contacts. Our experiments demonstrate that the system can achieve sub-second level response for large-scale contact tracing of tens of millions of people, with two magnitudes of performance boost over CPU based approach.