OVERVIEW For growing data volumes, how we manage data becomes more important. This session will cover the basics of managing data in a research environment such as those at ARC and nationally. Attendees of the course will be introduced to recommended tools for data sharing and transfer both on campus, off campus, and cloud. They […]
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, […]
OVERVIEW For growing data volumes, how we manage data becomes more important. This session will cover the basics of managing data in a research environment such as those at ARC and nationally. Attendees of the course will be introduced to recommended tools for data sharing and transfer both on campus, off campus, and cloud. They […]
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, […]
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 […]
OVERVIEW This workshop will provide a gentle introduction to using the multiprocessing package in Python for parallelizing and speeding up code. We will use hands-on programming exercises to demonstrate how to quickly get started with commonly used components of the multiprocessing package. Note that a Great Lakes account is optional for this workshop, but you […]
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, […]
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, […]
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 […]
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 […]