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Other literature type . 2024
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Conference object . 2024
License: CC BY
Data sources: Datacite
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Conference object . 2024
License: CC BY
Data sources: Datacite
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Application Performance for NASA Science

Authors: Kedziora, Gary;

Application Performance for NASA Science

Abstract

The Application Performance & Productivity (APP) Group at NASA provides NASA-affiliated scientists and engineers assistance with using the high-performance computing capabilities at NASA Advanced Supercomputing Division. This facility provides the computational power for generating accurate simulation data and state-of-the art analysis of large data sets to help meet NASA’s science mission. The APP Group’s mission is to enable users to use the systems effectively and efficiently. The application software infrastructure, largely built on open-source software such as Linux and government funded HPC libraries, provides high performance at the cost of complex build processes, with which we assist. Efficient use of the hardware, providing faster time to solution, lower cost, and lower power, is supported by providing services for application profiling and optimization. We have a history of fostering development of the HPC community through The NASA GPU Hackathon, and Winter Classic Invitational Student Cluster Competition, training, and direct assistance. Even with efforts such as these, a current challenge is to help the user-base adapt their software to using GPU-based computers to take advantage of these new capabilities. Efforts in these areas that leverage software and expertise from the DoE, NVIDIA, and others will be described.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green