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OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; workflow scripting using bash; high-throughput computing using launcher; parallel processing in one or more of Python, […] |
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OVERVIEW This workshop provides an introduction to processing CoreLogic data using PySpark on the Great Lakes cluster. The CoreLogic dataset contains aggregated data from individual, parcel-level real estate transactions and financial records. U-M has licensed access to Tax, Deed, and Foreclosure data at the parcel level for every county in the United States. We will […]
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OVERVIEW This workshop will go over methods and best practices for running machine learning applications on Great Lakes. We will briefly outline machine learning before stepping through a hands-on example problem to load a project and submit a job to the HPC cluster. Participants are expected to be familiar with Python, the command line, and […] |
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