TL;DR
The paper introduces DELTA, a framework enabling near real-time streaming analysis of large fusion data, allowing scientists to analyze and visualize plasma data promptly during experiments.
Contribution
DELTA's modular architecture and high-performance streaming capabilities facilitate real-time analysis and visualization of fusion data, a significant advancement over manual, delayed methods.
Findings
Achieves data transfer rates of about 500 MB/s.
Turbulence analysis distributed over multiple GPUs executes in under 5 minutes.
Integrates machine learning outputs with real-time visualization for better experiment decisions.
Abstract
While experiments on fusion plasmas produce high-dimensional data time series with ever increasing magnitude and velocity, data analysis has been lagging behind this development. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article we introduce the DELTA framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, DELTA allows to perform demanding data analysis tasks in between plasma pulses. This article describe the modular and expandable software architecture of DELTA and presents performance benchmarks of its individual components as well as of entire workflows. Our focus is on the streaming analysis of ECEi data measured at KSTAR on NERSCs supercomputers and we routinely achieve data…
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