https://github.com/cgc-umces/optimize-code-tutorials
Science Score: 13.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (6.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: CGC-UMCES
- Language: Python
- Default Branch: main
- Size: 310 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
This tutorial View the PDF provides guidance on optimizing data processing workflows on high-memory, multi-core systems. Using a case study of deciphering the CBP output, we demonstrate a parallelization strategy leveraging joblib to reduce processing time by distributing tasks across multiple cores and implementing efficient bulk I/O. Our approach significantly decreases compute and I/O times by accumulating data for a single write operation, reducing frequent disk writes, and balancing core usage.
For more details on the task purpose and serial code, see the documentation at https://github.com/CGC-UMCES/CBP-CDF.git.
Owner
- Name: CGC-UMCES
- Login: CGC-UMCES
- Kind: organization
- Email: cgc-github@umces.edu
- Location: United States of America
- Website: https://scipe.umces.edu
- Repositories: 1
- Profile: https://github.com/CGC-UMCES
Chesapeake Global Collaboratory (CGC) - University of Maryland Center for Environmental Science
GitHub Events
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- Push event: 7
- Create event: 1
Last Year
- Push event: 7
- Create event: 1