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DTSTART;TZID=America/Detroit:20220317T140000
DTEND;TZID=America/Detroit:20220317T160000
DTSTAMP:20220112T185149Z
CREATED:20220112T185149Z
LAST-MODIFIED:20220112T185149Z
UID:10000560-1647525600-1647532800@micde.umich.edu
SUMMARY:Machine Learning on Great Lakes
DESCRIPTION:OVERVIEW\n\n\nThis 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 basic Great Lakes functionality (logging in and navigating the directory structure). Participants must create a user account on Great Lakes prior to the workshop and are required to pre-register to gain access to a training account. \nINSTRUCTOR:\nMeghan Dailey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing \nMeghan Dailey is a machine learning specialist in the Advanced Research Computing (ARC) department at the University of Michigan. She consults on several faculty and student machine learning applications and research studies\, specializing in natural language processing and convolutional neural networks. Before her position at the university\, Ms. Richey worked for a defense contractor as a software engineer to design and implement software solutions for DoD-funded artificial intelligence efforts. \nA Zoom link will be provided to the participants the day before the class. Registration is required.\n\n\nInstructor will be available at the Zoom link\, to be provided\, from 1:00-2:00 PM for computer setup assistance. \nPlease note\, this session will be recorded.   \nTo register and view more details\, please refer to the linked TTC page. \n\nIf you have questions about this workshop\, please send an email to the instructor at richeym@umich.edu
URL:https://micde.umich.edu/event/https-ttc-iss-lsa-umich-edu-ttc-sessions-machine-learning-for-great-lakes-2/
LOCATION:Your Desktop
CATEGORIES:Data Science,Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220317T100000
DTEND;TZID=America/Detroit:20220317T120000
DTSTAMP:20230217T195820Z
CREATED:20220113T170314Z
LAST-MODIFIED:20230217T195820Z
UID:10000561-1647511200-1647518400@micde.umich.edu
SUMMARY:Processing the CoreLogic Data on Great Lakes using PySpark
DESCRIPTION:OVERVIEW\nThis 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 demonstrate how to request access to the dataset\, and how to quickly get started with processing and running some basic analytics on the data with the user-friendly\, browser-based Open OnDemand tool and the PySpark language on the cluster. \nNote that a Great Lakes account is required for this workshop\, and you must have an account before the start of the workshop in order to participate in the exercises. See below for account request information. \nINSTRUCTORS:\n\nArmand Burks\nResearch Data Scientist Intermediate\nInformation and Technology Services – Advanced Research Computing \nArmand Burks\, Ph.D.\, is a research data scientist intermediate for Advanced Research Computing – Technology Services (ARC-TS)\, a division of Information and Technology Services (ITS). Armand helps researchers with establishing data workflows\, transforming data between different formats\, programming support\, optimizing/parallelizing code\, cloud computing with Hadoop\, and developing custom code (C++\, Java\, Python). He earned a B.S. in computer science from Alabama State University in 2008\, an M.S. in computer science and engineering from Michigan State University in 2010\, and a Ph.D. in computer science from Michigan State University in 2017. \n  \nJule Krüger\nProgram Manager\nCenter for Political Studies\, Institute for Social Research and Information and Technology Services – Advanced Research Computing \n\nJule Krüger\, Ph.D.\, is the ISR Program Manager for Big Data and Data Science\, based within the Center for Political Studies at the Institute for Social Research\, and a member of the Advanced Research Computing Consulting Services.  She has more than 10 years of experience in processing\, analyzing and interpreting data for social science research\, and automating workflows for scalable\, auditable and reproducible analysis. \nMATERIALS \nPrerequisites: Participants will need an active Great Lakes account and login in order to complete hands-on exercises. Some familiarity with PySpark is helpful. \nFor more information on The Great Lakes cluster\, click here https://arc.umich.edu/greatlakes/. \nClick here to fill out an account request form https://arc.umich.edu/login-request \nNote: 3 business days are needed for creation of accounts \nStudents should fill in “Workshop” in the “Advisor” section. \nCampus VPN access is required for off-campus access to Great Lakes but not from on campus. An SSH client\, and Duo will be required during the workshop in order to use Great Lakes.  If you do not have this software already\, please download and install the Cisco AnyConnect VPN software following these instructions: https://its.umich.edu/enterprise/wifi-networks/vpn/getting-started You will need this to be able to use the ssh client. You will need to use the ‘Campus All traffic’ profile in the Cisco client. \nRegister here \nA Zoom link will be provided to the participants the day before the class. Registration is required. \nPlease note\, this session will be recorded.   \n\nIf you have questions about this workshop\, please send an email to the instructors at julianek@umich.edu \n 
URL:https://micde.umich.edu/event/processing-the-corelogic-data-on-great-lakes-using-pyspark/
LOCATION:Your Desktop
CATEGORIES:Great Lakes
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20220311T090000
DTEND;TZID=America/Detroit:20220311T120000
DTSTAMP:20220110T225518Z
CREATED:20220110T225518Z
LAST-MODIFIED:20220110T225518Z
UID:10000562-1646989200-1647000000@micde.umich.edu
SUMMARY:Advanced Research Computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \n\nTo register and view more details\, please refer to the linked TTC page.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2-2-3-2-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211022T130000
DTEND;TZID=America/Detroit:20211022T160000
DTSTAMP:20210930T201551Z
CREATED:20210930T201551Z
LAST-MODIFIED:20210930T201551Z
UID:10000532-1634907600-1634918400@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \n\nTo register and view more details\, please refer to the linked TTC page.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2-2-3/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211020T100000
DTEND;TZID=America/Detroit:20211020T113000
DTSTAMP:20230217T195752Z
CREATED:20211001T162623Z
LAST-MODIFIED:20230217T195752Z
UID:10000533-1634724000-1634729400@micde.umich.edu
SUMMARY:Getting Started with the Python Multiprocessing Package
DESCRIPTION:OVERVIEW\nThis 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 must have an account before the start of the workshop if you wish to use Great Lakes. See below for account request information. If you do not wish to use Great Lakes\, you must have python installed on your computer before the start of the workshop. \nINSTRUCTOR\nArmand Burks\nResearch Data Scientist Intermediate\nInformation and Technology Services – Advanced Research Computing \nArmand Burks\, Ph.D.\, is a research data scientist intermediate for Advanced Research Computing – Technology Services (ARC-TS)\, a division of Information and Technology Services (ITS). Armand helps researchers with establishing data workflows\, transforming data between different formats\, programming support\, optimizing/parallelizing code\, cloud computing with Hadoop\, and developing custom code (C++\, Java\, Python). He earned a B.S. in computer science from Alabama State University in 2008\, an M.S. in computer science and engineering from Michigan State University in 2010\, and a Ph.D. in computer science from Michigan State University in 2017. \nMATERIALS\nPrerequisites: Familiarity with connecting to the Great Lakes cluster via SSH/PuTTY and UMVPN\, Basic Linux command line familiarity\, basic programming experience in Python\, and an understanding of loops and basic data structures such as lists are all necessary for this hands-on workshop. \nFor more information on The Great Lakes cluster\, click here. \nClick here to fill out an account request form\nNote: 3 business days are needed for creation of accounts\nStudents should fill in “Workshop” in the “Advisor” section. \nCampus VPN access is required for off-campus access to Great Lakes but not from on campus. An SSH client\, and Duo will be required during the workshop in order to use Great Lakes.  If you do not have this software already\, please download and install the Cisco AnyConnect VPN software following these instructions: https://its.umich.edu/enterprise/wifi-networks/vpn/getting-started You will need this to be able to use the ssh client. You will need to use the ‘Campus All traffic’ profile in the Cisco client. \n  \nRegister here \nA Zoom link will be provided to the participants the day before the class. Registration is required. \nPlease note\, this session will be recorded. \nIf you have questions about this workshop\, please send an email to the instructor at arburks@umich.edu \n\n\n\nArmand R. Burks\, Ph. D. \nResearch Data Scientist\nAdvanced Research Computing\nSchool of Information\nUniversity of Michigan
URL:https://micde.umich.edu/event/https-ttc-iss-lsa-umich-edu-ttc-sessions-getting-started-with-the-python-multiprocessing-package/
LOCATION:Your Desktop
CATEGORIES:Data Science,Data Science Skills Series,Great Lakes,High Performance Computing,hpc-events,Info Session,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211014T140000
DTEND;TZID=America/Detroit:20211014T160000
DTSTAMP:20230217T195820Z
CREATED:20211001T161248Z
LAST-MODIFIED:20230217T195820Z
UID:10000536-1634220000-1634227200@micde.umich.edu
SUMMARY:Machine Learning on Great Lakes
DESCRIPTION:OVERVIEW\n\n\nThis 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 basic Great Lakes functionality (logging in and navigating the directory structure). Participants must create a user account on Great Lakes prior to the workshop and are required to pre-register to gain access to a training account. \nINSTRUCTORS\nMeghan Richey\nMachine Learning Specialist\nInformation and Technology Services – Advanced Research Computing \nMeghan Richey is a machine learning specialist in the Advanced Research Computing (ARC) department at the University of Michigan. She consults on several faculty and student machine learning applications and research studies\, specializing in natural language processing and convolutional neural networks. Before her position at the university\, Ms. Richey worked for a defense contractor as a software engineer to design and implement software solutions for DoD-funded artificial intelligence efforts. \nA Zoom link will be provided to the participants the day before the class. Registration is required.\n\n\nInstructor will be available at the Zoom link\, to be provided\, from 1:00-2:00 PM for computer setup assistance. \nPlease note\, this session will be recorded.   \nTo register and view more details\, please refer to the linked TTC page. \n\nIf you have questions about this workshop\, please send an email to the instructor at richeym@umich.edu
URL:https://micde.umich.edu/event/https-ttc-iss-lsa-umich-edu-ttc-sessions-machine-learning-for-great-lakes/
LOCATION:Your Desktop
CATEGORIES:Data Science,Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210917T130000
DTEND;TZID=America/Detroit:20210917T160000
DTSTAMP:20210810T215924Z
CREATED:20210810T215924Z
LAST-MODIFIED:20210810T215924Z
UID:10000509-1631883600-1631894400@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \n\n  \nPlease register at https://ttc.iss.lsa.umich.edu/ttc/sessions/advanced-research-computing-on-the-great-lakes-cluster-12/register/
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2-2-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210914T090000
DTEND;TZID=America/Detroit:20210914T103000
DTSTAMP:20260401T200107Z
CREATED:20210811T193429Z
LAST-MODIFIED:20260401T200107Z
UID:10000515-1631610000-1631615400@micde.umich.edu
SUMMARY:Data Sharing and Archiving
DESCRIPTION:OVERVIEW\n\n\nFor 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 will learn how to prepare data for archive\, including special high performance versions of tar and compression allowing significant performance benefits over the standard versions of the tools.\nLastly we will cover the properties and selection process of the appropriate general purpose  storage for data that requires long term preservation and active archiving that supports the largest data volumes in a way that controls costs and ease of management.\n\nRequirements are basic command line.
URL:https://micde.umich.edu/event/data-sharing-and-archiving-3-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210913T090000
DTEND;TZID=America/Detroit:20210913T120000
DTSTAMP:20260401T200048Z
CREATED:20210810T215550Z
LAST-MODIFIED:20260401T200048Z
UID:10000507-1631523600-1631534400@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
ORGANIZER;CN="Advanced Research Computing":MAILTO:arc-contact@umich.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210910T090000
DTEND;TZID=America/Detroit:20210910T103000
DTSTAMP:20260401T200019Z
CREATED:20210811T193025Z
LAST-MODIFIED:20260401T200019Z
UID:10000514-1631264400-1631269800@micde.umich.edu
SUMMARY:Data Sharing and Archiving
DESCRIPTION:OVERVIEW\n\n\nFor 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 will learn how to prepare data for archive\, including special high performance versions of tar and compression allowing significant performance benefits over the standard versions of the tools.\nLastly we will cover the properties and selection process of the appropriate general purpose  storage for data that requires long term preservation and active archiving that supports the largest data volumes in a way that controls costs and ease of management.\n\nRequirements are basic command line.
URL:https://micde.umich.edu/event/data-sharing-and-archiving-3/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210629T130000
DTEND;TZID=America/Detroit:20210629T130000
DTSTAMP:20210607T150210Z
CREATED:20210607T150210Z
LAST-MODIFIED:20210607T150210Z
UID:10000488-1624971600-1624971600@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nGreat Lakes Slurm HPC cluster\nGreat Lakes User Guide\nTwo-page Cheat Sheet\nMPI Profiling with Allinea MAP\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Great Lakes user login\, you don’t need to do anything.  Otherwise\, go to the Great Lakes user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need VPN software to access the U-M network.  If you do not have VPN software already installed\, please download and install the Cisco AnyConnect VPN software following these instructions.  You will need VPN to be able to use the ssh client to connect to Great Lakes. Please use the ‘Campus All traffic’ profile in the Cisco client. \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.  This document describes how to download and use this software\, except please note you will be connecting to greatlakes.arc-ts.umich.edu instead of the cited host.  You must have administrative authority over your computer to install this software.\nDownload PuTTY directly from the developer. Download the putty.exe application listed under “Alternative binary files\,”\, then execute the application.  You do not need administrative authority over your computer to use this software.\n\nOur Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes. \nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.Please note this session will be recorded. \n  \nPlease register at https://ttc.iss.lsa.umich.edu/ttc/sessions/advanced-research-computing-on-the-great-lakes-cluster-10/register/
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20210624T090000
DTEND;TZID=America/Detroit:20210624T120000
DTSTAMP:20210607T135434Z
CREATED:20210607T135434Z
LAST-MODIFIED:20210607T135434Z
UID:10000487-1624525200-1624536000@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nGreat Lakes Slurm HPC cluster\nGreat Lakes User Guide\nTwo-page Cheat Sheet\nMPI Profiling with Allinea MAP\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Great Lakes user login\, you don’t need to do anything.  Otherwise\, go to the Great Lakes user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need VPN software to access the U-M network.  If you do not have VPN software already installed\, please download and install the Cisco AnyConnect VPN software following these instructions.  You will need VPN to be able to use the ssh client to connect to Great Lakes. Please use the ‘Campus All traffic’ profile in the Cisco client. \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.  This document describes how to download and use this software\, except please note you will be connecting to greatlakes.arc-ts.umich.edu instead of the cited host.  You must have administrative authority over your computer to install this software.\nDownload PuTTY directly from the developer. Download the putty.exe application listed under “Alternative binary files\,”\, then execute the application.  You do not need administrative authority over your computer to use this software.\n\nOur Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes. \nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.Please note this session will be recorded. \n  \nPlease register at https://ttc.iss.lsa.umich.edu/ttc/sessions/advanced-research-computing-on-the-great-lakes-cluster-9/register/
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-7-2/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200930T130000
DTEND;TZID=America/Detroit:20200930T160000
DTSTAMP:20230905T171254Z
CREATED:20230905T171254Z
LAST-MODIFIED:20230905T171254Z
UID:10000416-1601470800-1601481600@micde.umich.edu
SUMMARY:Advanced research computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\n\n\nThis 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\, R\, and MATLAB; and profiling of parallel code using Allinea Performance Reports and Allinea MAP. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a member of the LSA Technology Services Research team at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes\nGreat Lakes Slurm HPC cluster\nGreat Lakes User Guide\nTwo-page Cheat Sheet\nMPI Profiling with Allinea MAP\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a user login\, a Slurm account\, and be enrolled in Duo. The user login allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The Slurm account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use to the account. Duo is required to help authenticate you to the cluster. \nUSER LOGIN\nIf you already have a Great Lakes user login\, you don’t need to do anything.  Otherwise\, go to the Great Lakes user login application page at: http://arc-ts.umich.edu/login-request/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nSLURM ACCOUNT\nWe create a Slurm account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Slurm account\, you can use that\, though if there are any issues with that account\, we will ask you to use the workshop account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou will need VPN software to access the U-M network.  If you do not have VPN software already installed\, please download and install the Cisco AnyConnect VPN software following these instructions.  You will need VPN to be able to use the ssh client to connect to Great Lakes. Please use the ‘Campus All traffic’ profile in the Cisco client. \nYou will need an ssh client to connect to the Great Lakes cluster. Mac OS X and Linux platforms have this built-in. Here are a couple of choices for Windows platforms: \n\nDownload and install U-M PuTTY/WinSCP from the Compute at the U website. This includes both the PuTTY ssh client and terminal emulator and a graphical file transfer tool in one installer.  This document describes how to download and use this software\, except please note you will be connecting to greatlakes.arc-ts.umich.edu instead of the cited host.  You must have administrative authority over your computer to install this software.\nDownload PuTTY directly from the developer. Download the putty.exe application listed under “Alternative binary files\,”\, then execute the application.  You do not need administrative authority over your computer to use this software.\n\nOur Great Lakes User Guide in Section 1.2 describes in more detail how to use PuTTY to connect to Great Lakes. \nPlease prepare and test your computer’s ability to make remote connections before class; we cannot stop to debug connection issues during the class. \n\nA Zoom link will be provided to the participants the day before the class. Registration is required.Please note this session will be recorded.
URL:https://micde.umich.edu/event/advanced-research-computing-on-the-great-lakes-cluster-4/
LOCATION:Your Desktop
CATEGORIES:Great Lakes,High Performance Computing,Workshops
END:VEVENT
END:VCALENDAR