Embedding Python for In-Situ Analysis
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
We describe our work to embed a Python interpreter in S3D, a highly scalable parallel direct numerical simulation reacting flow solver written in Fortran. Although S3D had no in-situ capability when we began, embedding the interpreter was surprisingly easy, and the result is an extremely flexible platform for conducting machine-learning experiments in-situ.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Sandia National Laboratories, Livermore, CA
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1734473
- Report Number(s):
- SAND--2018-9009; 667076
- Country of Publication:
- United States
- Language:
- English
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