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Title: Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems

Journal Article · · MRS Advances

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

References (1)

Fiji: an open-source platform for biological-image analysis journal June 2012