Abstract

The global nature of the ITER project along with its projected approximately petabyte-per-day data generation presents not only a unique challenge but also an opportunity for the fusion community to rethink, optimize, and enhance our scientific discovery process. Recognizing this, collaborative research with computational scientists was undertaken over the past several years to create a framework for large-scale data movement across wide-area networks to enable global near-real-time analysis of fusion data. This would broaden the available computational resources for analysis/simulation and increase the number of researchers actively participating in experiments.

An official demonstration of this framework for fast, large data transfer and real-time analysis was carried out between the KSTAR tokamak in Daejeon, Korea, and Princeton Plasma Physics Laboratory (PPPL) in Princeton, New Jersey. Streaming large data transfer, with near-real-time movie creation and analysis of the KSTAR electron cyclotron emission imaging data, was performed using the Adaptable Input Output (I/O) System (ADIOS) framework, and comparisons were made at PPPL with simulation results from the XGC1 code. These demonstrations were made possible utilizing an optimized network configuration at PPPL, which achieved over 8.8 Gbps (88% utilization) in throughput tests from the National Fusion Research Institute to PPPL.

This demonstration showed the feasibility for large-scale data analysis of KSTAR data and provides a nascent framework to enable use of globally distributed computational and personnel resources in pursuit of scientific knowledge from the ITER experiment.

摘要

国际热核实验堆项目的全球性质及其预计的每天约PB的数据生成不仅带来了独特的挑战，而且为融合界重新思考，优化和增强我们的科学发现过程提供了机会。认识到这一点，在过去的几年中与计算科学家进行了合作研究，以创建跨广域网进行大规模数据移动的框架，以实现融合数据的全球近实时分析。这将拓宽用于分析/模拟的可用计算资源，并增加积极参与实验的研究人员的数量。

韩国大田的KSTAR tokamak和新泽西州普林斯顿的普林斯顿等离子体物理实验室（PPPL）之间进行了这种快速，大量数据传输和实时分析框架的正式演示。使用适应性输入输出（I / O）系统（ADIOS）框架执行流式传输大数据传输，近实时电影制作和KSTAR电子回旋加速器发射成像数据分析，并在PPPL上进行了仿真比较XGC1代码的结果。通过在PPPL上使用优化的网络配置使这些演示成为可能，该网络配置在从国家融合研究院到PPPL的吞吐量测试中实现了8.8 Gbps以上（利用率88％）。

该演示展示了对KSTAR数据进行大规模数据分析的可行性，并提供了一个新生的框架，使人们能够利用全球分布的计算和人员资源来追求ITER实验的科学知识。