Leading magnetic fusion energy science into the big-and-fast data lane

Multimedia · Wed Jul 01 00:00:00 EDT 2020

DOI:https://doi.org/10.2172/1668037· OSTI ID:1668037

Kube, Ralph ^[1]; Churchill, R.M. ^[1]; Choi, JY; Wang, R; Klasky, S; Chang, C.S. ^[1]; Choi, MJ; Park, J

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1. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)

To crack the code of unlimited clean energy from magnetic fusion, researchers collaborate among numerous facilities that are scattered around the globe. Probing hot fusion plasmas with sophisticated diagnostics, they routinely generate fast streams of high-dimensional time-series data. We present the adaptation of a production code-base for a plasma diagnostic to the big-and-fast data lane. The new code-base is used to stream measurements, made in Korea, into a Top-15 computing facility in the US for remote analysis. We discuss software and design choices made for this new HPC-enabled scientific workflow.

• Research Organization: Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC02-09CH11466
• OSTI ID: 1668037
• Resource Relation: Conference: Scientific Computing with Python - SciPy 2020, July 6-12, 2020
• Country of Publication: United States
• Language: English