Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
In this work, we present the current status of a large-scale computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulations, and analyze these results using the state-of-the-art data analytics tools, machine learning, and uncertainty quantification methods using heterogeneous computing resources, such as CPU and GPU cluster. The framework can integrate or abstract out multiple domains based on roles. In order to develop this framework, we have leveraged an existing framework coupled with in-house heterogeneous computing resources. We present the results of using this framework on a single metadata triggered workflow to accelerate an additive manufacturing use case.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1605909
- Alternate ID(s):
- OSTI ID: 1657189
- Report Number(s):
- PNNL-SA-150139
- Journal Information:
- MRS Advances, Vol. 5, Issue 29-30; ISSN 2059-8521
- Publisher:
- Materials Research Society (MRS)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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