EAGER: Tensor500: A Streaming Analytics High Performance Computing Benchmark

大规模数据分析对于国家战略计算计划（NSCI）和NSF的科学发现任务至关重要。数据密集型超级计算应用程序对于处理高性能计算工作负载越来越重要。然而，当前的基准和性能度量并没有提供关于计算系统对数据密集型应用程序的适用性的有用信息。该项目将开发一个新的基准，可用于评估针对这类重要应用程序的新系统实现的性能。这项研究工作将产生一个新的Stream500基准，作为Graph500的补充，它可以复制流分析工作负载。通过使现有的基于web的基础设施能够接受多个基准测试的提交，当前的基准测试功能将得到扩展。该奖项反映了美国国家科学基金会的法定使命，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。

Large-scale data analytics is essential to the National Strategic Computing Initiative (NSCI) and NSF's scientific discovery mission. Data-intensive supercomputing applications are increasingly important for handling high-performance computing workloads. However, current benchmarks and performance metrics do not provide useful information on suitability of computing systems for data-intensive applications. This project will develop a new benchmark that can be used to assess the performance of new system implementations aimed at this important class of applications. The research effort will produce a new Stream500 benchmark, complementary to Graph500, that replicates streaming analytics workload. The current benchmark capabilities will be expanded by enabling the exiting web-based infrastructure to accept submissions for multiple benchmarks.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.