Task Parallelism to Optimize Performance of Environmental Modeling Software
- Univ. of New Mexico, Albuquerque, NM (United States)
Climate modeling is an integral part of environmental research, from studying rare phenomena to predicting future climate trends. The need for more accurate models is only growing, but as climate modeling capabilities advance, existing workflows require optimization to recoup performance. A solution comes in the form of task parallelism, a novel programming capability that provides an opportunity for optimization at execution time by allowing tasks to be executed in parallel, reducing runtime significantly. Using Parsl, an intuitive and scalable parallel scripting library for Python, we implement task parallelism within support software to aid in the continuous advancement of climate modeling technology.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- 89233218CNA000001
- OSTI ID:
- 1814747
- Report Number(s):
- LA-UR--21-28323
- Country of Publication:
- United States
- Language:
- English
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