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TZID:America/Detroit
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DTSTART:20180311T070000
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191101T140000
DTEND;TZID=America/Detroit:20191101T163000
DTSTAMP:20260605T225313
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000291-1572616800-1572625800@micde.umich.edu
SUMMARY:Intro to SQL
DESCRIPTION:Ever want to know how to communicate with a database? You need to know SQL\, a standard programming language for working with relational database management systems in data warehouses or just Microsoft Access. This workshop will cover the basic syntax of SQL. Material will focus mainly on how to query databases. A web-based tool will be used for the tutorial.
URL:https://micde.umich.edu/event/intro-to-sql-4-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191101T080000
DTEND;TZID=America/Detroit:20191101T130000
DTSTAMP:20260605T225313
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000281-1572595200-1572613200@micde.umich.edu
SUMMARY:NSF Computational Mechanics Vision Workshop
DESCRIPTION:Boston University\, Duke University\, and the University of Michigan have organized the 2019 Computational Mechanics Workshop to solicit and synthesize directions for computational mechanics research and education in the United States over the next decade and beyond from a diverse cross section of scientists and engineers. Topics to discuss include the following four broad themes: machine learning/big data\, manufacturing\, risk/uncertainty engineering (including climate\, infrastructure\, natural disasters\, etc.)\, and medicine. \nParticipants\nWorkshop is open to all interested faculty. If you’re interested in attending\, please contact us at micde-events@umich.edu to reserve your spot.
URL:https://micde.umich.edu/event/nsf-computational-mechanics-vision-workshop-nov/
LOCATION:Rackham Amphitheatre\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Amphitheatre 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191031T080000
DTEND;TZID=America/Detroit:20191031T170000
DTSTAMP:20260605T225313
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000275-1572508800-1572541200@micde.umich.edu
SUMMARY:NSF Computational Mechanics Vision Workshop
DESCRIPTION:Boston University\, Duke University\, and the University of Michigan have organized the 2019 Computational Mechanics Workshop to solicit and synthesize directions for computational mechanics research and education in the United States over the next decade and beyond from a diverse cross section of scientists and engineers. Topics to discuss include the following four broad themes: machine learning/big data\, manufacturing\, risk/uncertainty engineering (including climate\, infrastructure\, natural disasters\, etc.)\, and medicine. \nParticipants\nWorkshop is open to all interested faculty. If you’re interested in attending\, please contact us at micde-events@umich.edu to reserve your spot.
URL:https://micde.umich.edu/event/nsf-computational-mechanics-vision-workshop/
LOCATION:Rackham Amphitheatre\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Amphitheatre 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191030T130000
DTEND;TZID=America/Detroit:20191030T160000
DTSTAMP:20260605T225313
CREATED:20230905T171300Z
LAST-MODIFIED:20230905T171300Z
UID:10000295-1572440400-1572451200@micde.umich.edu
SUMMARY:Research Computing on the Great Lakes Cluster
DESCRIPTION:OVERVIEW\nThis workshop will provide a brief overview of the components of the Great Lakes Cluster. The main body of the workshop will cover the resource manager and scheduler\, creating submissions scripts to run jobs and the options available in them\, and hands-on experience. By the end of the workshop\, every participant should have created a submission script\, submitted a job\, tracked its progress\, and collected its output. Participants will have several working examples from which to build their own submissions scripts in their own home directories. \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 High Performance Computing Consultant in the Research Computing Services group of LSA TS 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 \nMark Champe\nResearch Computing Services\nLSA Technology Services \nMATERIALS\nLecture notes\nGreat Lakes HPC cluster \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 don’t already have a Great Lakes user login\, please visit the application page. \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. \nLAPTOP PREPARATION\nYou do not need to bring your own laptop to class. The classroom will provide Windows or Mac computers\, which require your uniqname and UMICH (AKA Level 1) password to login\, and that have all necessary software pre-loaded. \nIf you want to use a laptop for the course\, you are welcome to do so: please see our web page on Preparing your laptop to use Flux (those instructions apply to Great Lakes as well). However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We cannot stop to debug connection issues with personal or departmental laptops during the class.
URL:https://micde.umich.edu/event/research-computing-on-the-great-lakes-cluster-5/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191028T160000
DTEND;TZID=America/Detroit:20191028T160000
DTSTAMP:20260605T225313
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000297-1572278400-1572278400@micde.umich.edu
SUMMARY:Mid West Mechanics Seminar: Jacqueline H. Chen\, Senior Scientist\, Sandia National Laboratories
DESCRIPTION:Bio: Jacqueline H. Chen is a Senior Scientist at the Combustion Research Facility at Sandia National Laboratories. She has contributed broadly to research in turbulent combustion elucidating turbulence-chemistry interactions in combustion through direct numerical simulations. To achieve scalable performance of DNS on heterogeneous computer architectures she leads an interdisciplinary team of computer scientists\, applied mathematicians and computational scientists to develop an exascale direct numerical simulation capability for turbulent combustion with complex chemistry and multi- physics. She is a member of the National Academy of Engineering and a Fellow of the Combustion Institute and the Americal Physical Society. She received the Combustion Institute’s Bernard Lewis Gold Medal Award in 2018 and the Society of Women Engineers Achievement Award in 2018. \nTowards Exascale Simulation of Turbulent Combustion in Complex Flows Relevant to Efficient Clean Engines\nDirect numerical simulation (DNS) methodology and computing power have progressed to the point where it is feasible to perform DNS in mildly complex geometries representative of flow configurations encountered in practical combustors. These complex flows encompass effects of mean shear\, flow recirculation\, and wall boundary layers together with turbulent fluctuations which affect entrainment\, mixing and combustion. Recent DNS studies with complex flows relevant to efficient low emissions gas turbine and internal combustion engines will be presented. Through application co-design with computer scientists a data centric asynchronous programming system has been used to refactor the DNS code\, S3D\, resulting in improved time-to-solution and overall performance on heterogeneous architectures. The programming system also provides more efficient and effective composition of in situ analytics and machine learning techniques. \nContact Melissa McGeorge (mcgeorge@umich.edu) for more details.
URL:https://micde.umich.edu/event/mid-west-mechanics-seminar-jacqueline-h-chen-sandia-national-laboratories/
LOCATION:107 Gorguze Family Laboratory\, 2609 Draper Dr\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2023/02/JacquelineChen.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191024T170000
DTEND;TZID=America/Detroit:20191024T190000
DTSTAMP:20260605T225313
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000293-1571936400-1571943600@micde.umich.edu
SUMMARY:SC2 Workshop Series: Intro to Jugular: Virtual Reality and 3D Rendering
DESCRIPTION:Learn how to format\, load and visualize your data in 3D. Jugular works in U-M M.I.D.E.N.\, the Occulus Rift and any desktop window. The U-M 3D Lab will teach this workshop and show us the available tools in-house. This workshop is part of the Scientific Computing Student Club’s (SC2) 2020 Visualization Challenge. Learn more about the workshop series and the Visualization Challenge here. \nInstructor: Theodore Hall\, U-M 3D Lab\, The Duderstadt Center \nSpace is limited. Register here.
URL:https://micde.umich.edu/event/sc2-workshop-series-intro-to-jugular-virtual-reality-and-3d-rendering/
LOCATION:U-M 3D Lab\, Digital Media Commons\, Duderstadt Center\, 2281 Bonisteel Blvd\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,SC2,Workshops
GEO:42.291072;-83.715734
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=U-M 3D Lab Digital Media Commons Duderstadt Center 2281 Bonisteel Blvd Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2281 Bonisteel Blvd:geo:-83.715734,42.291072
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191023T100000
DTEND;TZID=America/Detroit:20191023T120000
DTSTAMP:20260605T225313
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000284-1571824800-1571832000@micde.umich.edu
SUMMARY:Introduction to Performance Analysis of Scientific Software
DESCRIPTION:We all had this: “My program is too slow”. We all have heard: “Use Fortran and C++\, they are fast.”  But will it really help? We all have heard also: “Don’t bother\, use Python and R on a better computer”\, and “HPC clusters are fast”.  But what does “better” and “fast” even mean? In this workshop\, we will observe\, measure and discuss performance behavior of various scientific workloads\, and learn about typical performance classes and basic performance measuring methodology.  In the end\, you will be able to classify your expected workload and make an educated guess whether changing the programming language\, upgrading the computer\, or applying for cluster computing time would likely be advantageous. \n  \nRequirements: If you wish to follow hands-on demonstrations\, you will need to bring your own laptop and have a UMich account.
URL:https://micde.umich.edu/event/introduction-to-performance-analysis-of-scientific-software/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191018T150000
DTEND;TZID=America/Detroit:20191018T163000
DTSTAMP:20260605T225313
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000286-1571410800-1571416200@micde.umich.edu
SUMMARY:Mediation Models: A demonstration using multiple packages
DESCRIPTION:Mediation models are commonly applied in a variety of modeling settings\, and people will typically flock to tools specific to structural equation modeling like Mplus or Amos for analysis.  However\, not only are such tools not necessary for the more common implementations of mediation\, they are often limiting and have various drawbacks. \n\nFortunately there are a variety of packages in R that can do mediation analysis\, often using straightforward code and familiar models or other tools.  This presentation will demonstrate a variety of ways in which to do a standard mediation model in R (and Python)\, and discuss the available complexities that can be handled with the tools\, as well as their corresponding strengths and weaknesses.\n\nNote that this is not an introduction to mediation analysis\, but is a demonstration of tools.  Some familiarity with R and mediation models will be assumed.
URL:https://micde.umich.edu/event/mediation-models-a-demonstration-using-multiple-packages-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191018T130000
DTEND;TZID=America/Detroit:20191018T143000
DTSTAMP:20260605T225313
CREATED:20230905T171336Z
LAST-MODIFIED:20230905T171336Z
UID:10000278-1571403600-1571409000@micde.umich.edu
SUMMARY:Back to a Future: Asynchronous Computing with futures in R
DESCRIPTION:Asynchronous computing is an umbrella term encompassing parallel and concurrent computational programs in which some tasks can be executed without a strict sequential order.  A future is a programming abstraction for a value that may be available at some future point in time and allows.  Like other forms of parallelism\, futures are a powerful tool for writing programs that efficiently make use of available computing resources.  At the same time\, futures can also be used to make interactive data analyses more time efficient.  \n In this workshop\, we’ll discuss futures as implemented in the R package “future” and provide example use cases for both interactive analysis and batch processing.  
URL:https://micde.umich.edu/event/back-to-a-future-asynchronous-computing-with-futures-in-r/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191017T113000
DTEND;TZID=America/Detroit:20191017T123000
DTSTAMP:20260605T225313
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000247-1571311800-1571315400@micde.umich.edu
SUMMARY:MICDE Seminar: Janet Scheel\, Associate Professor\, Physics\, Occidental College
DESCRIPTION:Bio: Dr. Scheel has taught at a variety of higher education institutions\, including California Lutheran University\, Caltech\, and Cornell University. She also conducted research at Cal Lutheran\, Caltech\, Cornell\, and Argonne National Laboratory. She is coauthor of Analytical Mechanics\, an advanced undergraduate physics textbook. She is currently a Mercator Fellow as a part of the Priority Programme SPP 1881 of the Deutsche Forschungsgemeinschaft. Janet Scheel’s research deals with pattern formation and turbulence. The particular system she studies is Rayleigh-Benard convection. \nNumerical Simulations of Turbulence in Heated Fluids\nTurbulent systems are all around us\, from waves crashing on our beaches\, to smoke rising from the fires in our mountains\, to the air that can disrupt our smooth airline flights. But\, turbulent systems are not well understood. Rayleigh-Benard Convection is a more simplified system which captures some of the key features of turbulence\, including thermal plumes\, thin boundary layers and large-scale flow. In Rayleigh-Benard convection\, an enclosed fluid is bounded by horizontal parallel plates kept at a constant temperature difference. Results from numerical simulations of the equations which describe Rayleigh-Benard convection will be discussed and compared to experimental and theoretical results. These include flows in air and liquid metals in confined containers in addition to more horizontally extended systems. \nThis seminar is jointly sponsored with the department of Complex Systems. Prof. Scheel is being hosted by Prof. Doering (Complex Systems\, Mathematics and Physics). If you would like to meet with her during her visit\, please send an email to micde-events@umich.edu. If you are an MICDE students and would like to join Prof. Scheel for lunch\, please RSVP  by October 15th. 
URL:https://micde.umich.edu/event/fall2019-scheel-occidentalcollege/
LOCATION:Weiser Hall\, Room 747\, 500 Church St\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Janet-Scheel.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191016T133000
DTEND;TZID=America/Detroit:20191016T163000
DTSTAMP:20260605T225313
CREATED:20230905T171337Z
LAST-MODIFIED:20230905T171337Z
UID:10000283-1571232600-1571243400@micde.umich.edu
SUMMARY:Geometric Network Analysis
DESCRIPTION:This workshop will cover GIS concepts and techniques for analyzing geometric networks embedded in geographical space. We will mainly focus on road network\, but the ideas and techniques apply to similar network such as the water and electricity distribution networks and gas pipelines. We will use open source tools in R and QGIS. \nYou should know the introductory concepts and tools in GIS and should be familiar with R. Familiarity with QGIS is not required.
URL:https://micde.umich.edu/event/geometric-network-analysis/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191015T100000
DTEND;TZID=America/Detroit:20191015T120000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000268-1571133600-1571140800@micde.umich.edu
SUMMARY:Introduction to NumPy (Python)
DESCRIPTION:This workshop will introduce you to the NumPy library in Python\, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth\, along with related linear algebra and random number capabilities. Some familiarity with Python is expected. Computers will be available to complete exercises.
URL:https://micde.umich.edu/event/introduction-to-numpy-python/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191011T140000
DTEND;TZID=America/Detroit:20191011T163000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000287-1570802400-1570811400@micde.umich.edu
SUMMARY:Web Scraping with Python
DESCRIPTION:This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests\, beautifulsoup\, and retry modules with the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3 will be used.
URL:https://micde.umich.edu/event/web-scraping-with-python-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20191010T150000
DTEND;TZID=America/Detroit:20191010T160000
DTSTAMP:20260605T225313
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000246-1570719600-1570723200@micde.umich.edu
SUMMARY:MICDE Seminar: Ali Yilmaz\, Professor\, Electrical and Computer Engineering\, The University of Texas at Austin
DESCRIPTION:Bio: Ali Yilmaz is a Professor of Electrical and Computer Engineering and a core faculty member at the Institute for Computational Engineering and Sciences at the University of Texas at Austin. Dr. Yilmaz received the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2005. He spent 2005 to 2006 as a post-doctoral research associate with the Center for Computational Electromagnetics at the University of Illinois; in 2006\, he joined the faculty of The University of Texas at Austin. His research interests include computational electromagnetics (particularly fast frequency- and time-domain integral equation solvers)\, parallel algorithms\, antenna and scattering analysis\, bioelectromagnetics\, geoelectromagnetics\, and electronic packages. He has authored or co-authored over 170 papers in refereed journals and international conferences on these topics. \nUsing (Super)Computers Judiciously for Higher Fidelity Electromagnetic Analysis\nIncreasing the fidelity of the electromagnetic models generally increases the predictive power of the analyses based on the models. It also generally increases the results’ sensitivity to model features/parameters as well as the difficulty of constructing the models\, accurately solving the governing equations\, and interpreting the resulting data. Therefore\, one should base the analysis on the lowest-fidelity model one can get away with or\, equivalently\, the highest-fidelity model one can afford. The sweet spot for the tradeoff\, “the appropriate model”\, has changed over time in part because past successes in simulation-based science and engineering have increased expectations/requirements from electromagnetic analysis and in part because tremendous improvements in computing infrastructure and advances in computational methods have increased the affordability of complex analysis. Finding the appropriate model requires understanding both the benefits and the costs of analysis when a lower- or higher-fidelity model is used; neither side of the ledger\, however\, is known beforehand (unless one is repeating previously established analyses). A possible approach to revealing these unknowns is to construct models by gradually increasing their fidelity\, performing analysis at each fidelity level\, and comparing the analysis results and costs to those from the previous steps. I will show examples of this “analysis-driven modeling” in bioelectromagnetics (using the AustinMan and AustinWoman human body models) and signal integrity (using an electronic package example) by employing parallel algorithms and advanced integral-equation solvers on leading-edge supercomputers. \n The examples will highlight many of the challenges arising from this approach to modeling. An important one is that “the appropriate method” of analysis generally depends on the model\, e.g.\, a method can outperform alternatives for low-fidelity models but underperform them for high-fidelity ones; indeed\, inappropriate (but convenient) methods can not only inflate the cost side of the ledger but also deflate the benefit side\, leading to misjudgment of the appropriate model fidelity. Thus\, not surprisingly\, the development of appropriate electromagnetic models and appropriate computational methods are tightly linked (aka “if all you have is a hammer\, everything looks like a nail”). Unfortunately\, evaluating computational methods to find the appropriate one for a given model is surprisingly difficult\, even for unbiased experts\, as method performances depend not just on the models but also on the computers\, the software realizations of the methods\, and the users/developers of the software. On the one hand\, theoretical comparisons (e.g.\, of asymptotic complexities\, error convergence rates\, parallel scalability limits) are often incapable of factoring in the large impact of software and hardware infrastructure on the realized/observed performance of a computational method—a problem that has worsened as the traditional Dennard scaling of clock frequencies ended in the last decade. On the other hand\, empirical comparisons are beset by the same problems that physical measurements face (including irreproducible and uncertain results)\, require many (potentially low-efficiency) computations\, and suffer from the large number of alternative methods. I will discuss whether benchmark suites can improve the judicious use of computational methods for electromagnetic analysis and what the necessary ingredients for such benchmarks are. \nProf. Yilmaz is being hosted by Prof. Michielssen (EECS). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE students\, or a EEC graduate student\, and would like to join Prof. Yilmaz for lunch\, please RSVP here by October 8th.  \n 
URL:https://micde.umich.edu/event/fall2019-yilmaz-utaustin/
LOCATION:1008 FXB\, 1320 Beal Ave\, Ann Arbor\, MI\, 48109
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Ali-Yilmaz.png
GEO:42.2934832;-83.7119819
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1008 FXB 1320 Beal Ave Ann Arbor MI 48109;X-APPLE-RADIUS=500;X-TITLE=1320 Beal Ave:geo:-83.7119819,42.2934832
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190930T130000
DTEND;TZID=America/Detroit:20190930T160000
DTSTAMP:20260605T225313
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000265-1569848400-1569859200@micde.umich.edu
SUMMARY:Data Visualization With 3D Graphics Using Unity3D and C#
DESCRIPTION:Video game development is more accessible than ever before thanks to modern software tools\, with many options free to download. These tools are also used to program more “serious” applications that require interactive 3D graphics\, from mobile apps\, virtual and augmented reality\, computer vision and artificial intelligence\, and real-time CGI film production.  \n  \nUnity3D is a powerful and popular game engine for both hobbyist and professional projects\, able to compile a ‘game’ to almost any computer platform\, and free to download for non-commercial use. This workshop will show how you can use it to render data from research projects in a 3D interactive representation for user analysis and demonstration. \n  \nIn this workshop\, we introduce the Unity3D workspace\, and prepare a demo that allows the user to load an example dataset and view it as a simple set of 3D representations. A basic familiarity with computer programming (C# will be used during the session) is recommended to get the most out of the workshop. To take part\, users will be responsible to bring their own laptop with Unity3D (available for Windows\, Macintosh and Linux) pre-installed. Additional project files will be provided to registered users ahead of the workshop date.
URL:https://micde.umich.edu/event/data-visualization-with-3d-graphics-using-unity3d-and-c/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190930T110000
DTEND;TZID=America/Detroit:20190930T120000
DTSTAMP:20260605T225313
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000245-1569841200-1569844800@micde.umich.edu
SUMMARY:MICDE Seminar: Jason MacLean\, Associate Professor\, Neurobiology\, University of Chicago
DESCRIPTION:Bio: Jason MacLean is an Associate Professor in the Department of Neurobiology and director of undergraduate studies in neuroscience at the University of Chicago.  His research aims to define how information is encoded in the brain by large groups of synaptically interconnected neurons using a range of analytical approaches. He complements this work by simulating and training spiking neuronal networks. Jason completed his Ph.D. at the University of Manitoba in Canada\, and worked at Cornell University and Columbia University before establishing his own group at the University of Chicago in 2008. He and his wife have two children and he no longer has time for hobbies. \nRecurrent interactions can explain the variance in single trial responses\nTo develop a complete description of sensory encoding\, it is necessary to account for trial-to-trial variability in cortical neurons. Using a generalized linear model with terms corresponding to the visual stimulus\, mouse running speed\, and experimentally measured neuronal correlations\, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically\, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups\, in encoding and decoding frameworks\, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials. \nProf. MacLean is being hosted by Prof. Watson (Psychiatry). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student and would like to join Prof. MacLean for lunch please RSVP by Saturday\, September 28th. 
URL:https://micde.umich.edu/event/fall2019-maclean-uchicago/
LOCATION:Weiser Hall\, Room 555\, 500 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Jason-MacLean.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190927T140000
DTEND;TZID=America/Detroit:20190927T160000
DTSTAMP:20260605T225313
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000269-1569592800-1569600000@micde.umich.edu
SUMMARY:Stata 16 New Data Management Features
DESCRIPTION:Audience: Stata users familiar with data management who want an overview of the new data management features introduced in Stata 16.\n\nWe’ll cover the two main data management features introduced in Stata 16.\n\n1) Frames – holding multiple data sets in memory simultaneously.\n2) Variable lists – formalizing creation and storage of lists of variables.
URL:https://micde.umich.edu/event/stata-16-new-data-management-features/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190926T133000
DTEND;TZID=America/Detroit:20190926T163000
DTSTAMP:20260605T225313
CREATED:20230905T171405Z
LAST-MODIFIED:20230905T171405Z
UID:10000282-1569504600-1569515400@micde.umich.edu
SUMMARY:Open Source GIS
DESCRIPTION:This workshop will provide a gentle introduction to open source GIS tools in R and QGIS. We will cover introductory GIS concepts and will explore the functionalities of R and QGIS for manipulating and analyzing vector GIS data. Familiarity with R is required.
URL:https://micde.umich.edu/event/open-source-gis-3/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190926T130000
DTEND;TZID=America/Detroit:20190926T160000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000277-1569502800-1569513600@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \n  \nInstructor\nKenneth Weiss\nIT Project Senior Manager\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMaterials\n\nLecture Notes (updated Sept. 21\, 2017)\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCourse Preparation\nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems.
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-8-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190926T130000
DTEND;TZID=America/Detroit:20190926T160000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000263-1569502800-1569513600@micde.umich.edu
SUMMARY:Research Computing on the Great Lakes cluster
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/research-computing-on-the-great-lakes-cluster-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190925T150000
DTEND;TZID=America/Detroit:20190925T160000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000244-1569423600-1569427200@micde.umich.edu
SUMMARY:MICDE Seminar: H. Metin Aktulga\, Assistant Professor\, Computer Science and Engineering\, Michigan State University
DESCRIPTION:Bio: H. Metin Aktulga received his B.S. degree from Bilkent University in 2004\, M.S. and Ph.D. degrees from Purdue University in 2009 and 2010\, respectively; all in Computer Science. Before joining the Michigan State University (MSU) in 2014\, he was a postdoctoral researcher in the Computational Research Division at the Lawrence Berkeley Lab. He directs the Scalable Parallel Technologies and Algorithms (SParTA) Lab at MSU. Research in the SParTA Lab focuses on HPC and applications of HPC\, specifically on the design and development of algorithms\, numerical methods and software systems that can harness the full potential of state-of-the-art computing platforms to address challenging problems in large scale scientific computations and big-data analytics problems. Dr. Aktulga’s research is supported by NSF\, DOE\, AFRL\, NIH and the MSU Foundation. He is the recipient of the NSF CAREER award in 2019. \nTowards Fast\, Scalable and High Fidelity Reactive Molecular Dynamics Simulations\nReactive molecular dynamics (RMD) models bridge quantum-scale and classical MD approaches by explicitly modeling bond activity and redistribution of charges. As such they enable the study of important phenomena which otherwise is impractical using classical or quantum techniques. However\, RMD models have a significantly complex formulation\, making fast\, scalable and high fidelity RMD simulations extremely challenging to achieve. In this talk\, I will present our work towards addressing both the scalability and fidelity challenges. I will start by describing the parallel algorithms and numerical techniques that we developed for a fast implementation of the Reax Force Field (ReaxFF)\, which is used by hundreds of researchers worldwide. Particular emphasis will be on novel solvers we recently developed for the dynamic charge distribution problem that constitutes the most important scalability bottleneck in large RMD simulations. I will conclude the talk by outlining our efforts towards addressing the fidelity challenge\, i) through an automated force field framework for RMD models\, ii) by developing a novel hybrid ReaxFF/AMBER simulation software in the spirit of QM/MM techniques. \nProf. Aktulga is being hosted by the Glotzer Lab (Chemical Engineering). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE students\, or a Chemical Engineering graduate student\, and would like to join Prof. Aktulga for lunch\, please RSVP here by September 23rd.  \n 
URL:https://micde.umich.edu/event/fall2019-aktulga-msu/
LOCATION:1303 EECS\, 1301 Beal Ave\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2019/07/Metin-Aktulga.png
GEO:42.292322;-83.713272
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1303 EECS 1301 Beal Ave Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=1301 Beal Ave:geo:-83.713272,42.292322
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190925T093000
DTEND;TZID=America/Detroit:20190925T160000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000270-1569403800-1569427200@micde.umich.edu
SUMMARY:Introduction to Stata
DESCRIPTION: Audience: Those who have never used Stata before but wish to learn.\n\nBy the end of the workshop\, participants will be able to:\n\n\nWork with Stata\, including using Do-files and using the help system\nGet data into Stata and manage your data files\nEstablish familiarity with your data\nClean the data to prepare it for analysis\nCheck for basic errors in the data\nGenerate new variables or manipulate existing variables\nMerge or reshape the data\nProduce summary tables and descriptive statistics\n\n\nNote: This workshop does NOT cover any statistical modeling.\n\nNote: This workshop is based on Stata 15; it does not cover the new features in Stata 16.\nSee upcoming workshop “Stata 16 New Data Management Features” for that material.
URL:https://micde.umich.edu/event/introduction-to-stata-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190924T160000
DTEND;TZID=America/Detroit:20190924T170000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000274-1569340800-1569344400@micde.umich.edu
SUMMARY:Graduate Studies in Computational & Data Sciences Info Session – North Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Computational Neuroscience trains the next generation of interdisciplinary neuroscientists. The certificate program is open to all students pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/info-session-fall2019-north/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor LEC 3213ABC\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Info Session
GEO:42.2914823;-83.7138452
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Johnson Rooms Lurie Engineering Center 3rd Floor LEC 3213ABC 1221 Beal Ave. Ann Arbor MI United States;X-APPLE-RADIUS=500;X-TITLE=1221 Beal Ave.:geo:-83.7138452,42.2914823
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190924T090000
DTEND;TZID=America/Detroit:20190924T170000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000079-1569315600-1569344400@micde.umich.edu
SUMMARY:Introduction to SPSS
DESCRIPTION:Audience: Never before SPSS users who will be using SPSS for Windows.  Those using SPSS for Unix or Macintosh should email the instructor at cpow@umich.edu before enrolling. \nFundamentals \nThis portion introduces SPSS for Windows\, the menu and the help systems\, the three main types of files used\, and printing from within SPSS.  It then addresses defining variables\, attaching labels\, defining missing values\, and various ways to enter data into SPSS.  Finally\, it covers a brief introduction to obtaining frequency distributions\, descriptive statistics\, and cross tabulations of variables. \nWithin-Case Transformations \nThis portion introduces data management capabilities\, including recoding variables (manual and automatic)\, computing new variables using formulas\, and counting occurrences of values within subjects.  Attention then turns to temporary transformations\, conditional processing of transformations\, and repetitive transformations.  SPSS syntax is also introduced. \nData Management with Multiple Files \nThis portion begins with a discussion of subsetting data files by drawing samples\, selecting groups and excluding groups from analysis.  Then\, the two main methods of merging SPSS data files are covered: adding additional variables and adding additional cases.  Next\, creating aggregated data sets and applying aggregated data to individuals is covered.  Lastly\, importing and exporting data between SPSS and other statistical programs (Excel\, dBase\, SAS) is demonstrated. \nBasic Statistics and Graphics\nThis portion covers basic exploratory procedures\, including obtaining percentiles\, frequencies\, descriptive statistics\, and cross tabulations. Basic comparative procedures including two-sample t-tests\, paired t-tests\, and one-way analysis of variance are also covered.  Then\, simple bivariate correlation analysis is introduced.  Participants are given a basic introduction to commonly used graphical procedures for displaying data\, including scatter plots\, bar graphs\, histograms\, and boxplots.
URL:https://micde.umich.edu/event/introduction-to-spss-2-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190923T170000
DTEND;TZID=America/Detroit:20190923T180000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000273-1569258000-1569261600@micde.umich.edu
SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - Central Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Computational Neuroscience trains the next generation of interdisciplinary neuroscientists. The certificate program is open to all students pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/info-session-fall2019-central/
LOCATION:Weiser Hall\, Room 110 (First Floor)\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190923T130000
DTEND;TZID=America/Detroit:20190923T160000
DTSTAMP:20260605T225313
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
UID:10000280-1569243600-1569254400@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \nINSTRUCTOR \nKenneth Weiss\nIT Project Senior Manager\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMATERIALS \n\nLecture Notes\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCOURSE PREPARATION \nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems. \n\nIf you have questions about this workshop\, please send an email to the instructor at kgweiss@umich.edu
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-9/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190920T150000
DTEND;TZID=America/Detroit:20190920T163000
DTSTAMP:20260605T225313
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
UID:10000272-1568991600-1568997000@micde.umich.edu
SUMMARY:Data management in R with data.table
DESCRIPTION:Matt Dowle\, author of the data.table package\, describes it as\, “provid[ing] a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use\, convenience and programming speed.” In this workshop I will first introduce the data.table syntax using generic SQL and the dplyr R package as reference points.  Topics to be discussed include subsetting\, aggregating\, and merging data frames.  I will then discuss updating by reference and its role in efficiently working with large data sets.  Other advanced uses of the powerful data.table syntax will be covered as time permits. \nIf you have questions about this workshop\, please send an email to jbhender@umich.edu
URL:https://micde.umich.edu/event/data-management-in-r-with-data-table-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001B
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190920T130000
DTEND;TZID=America/Detroit:20190920T160000
DTSTAMP:20260605T225313
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
UID:10000262-1568984400-1568995200@micde.umich.edu
SUMMARY:Research Computing on the Great Lakes cluster
DESCRIPTION:This workshop will provide a brief overview of the the new HPC environment and is intended for current Flux and Armis users.  We will use the temporary Beta HPC cluster to demonstrate how jobs will be submitted and managed under the new Great Lakes\, Armis2\, and Lighthouse clusters available later this year. \nThere are many differences between the familiar Flux environment and that of the new HPC clusters\, including a new batch scheduling system\, a new interactive batch job environment\, a new HPC web portal\, a new module environment\, and a new on-demand-only job accounting system. \nWe will cover these differences in the workshop\, and provide hands-on training in creating and running job submission scripts in the new HPC environment.  Students are expected to be conversant with the Linux command line and have experience in creating\, submitting\, and troubleshooting PBS batch scripts.
URL:https://micde.umich.edu/event/research-computing-on-the-great-lakes-cluster-3/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190920T090000
DTEND;TZID=America/Detroit:20190920T120000
DTSTAMP:20260605T225313
CREATED:20230905T171403Z
LAST-MODIFIED:20230905T171403Z
UID:10000276-1568970000-1568980800@micde.umich.edu
SUMMARY:Introduction to the Linux Command Line
DESCRIPTION:This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell\, also generically referred to as “the command line”. Topics include: a brief overview of Linux\, the Bash shell\, navigating the file system\, basic commands\, shell redirection\, permissions\, processes\, and the command environment. The workshop will also provide a quick introduction to nano a simple text editor that will be used in subsequent workshops to edit files. \n  \nInstructor\nKenneth Weiss\nIT Project Senior Manager\nMedical School Information Services (MSIS) \nKen is a High Performance Computing Consultant in the Computational Research Consulting Division of MSIS at the University of Michigan. He works with a team of IT specialists to provide high performance computing support and training for the Medical School. Prior to this\, he spent 21 years managing research computing\, including an HPC cluster\, for Dr. Charles Sing in the Human Genetics Department. \nMaterials\n\nLecture Notes (updated Sept. 21\, 2017)\nReference text: William E Shotts\, Jr.\, “The Linux Command Line: A Complete Introduction\,” No Starch Press\, January 2012 .http://linuxcommand.org/tlcl.php\nDownload Creative Commons Licensed version at http://downloads.sourceforge.net/project/linuxcommand/TLCL/13.07/TLCL-13.07.pdf\n\n\nCourse Preparation\nYou must register at least three full days prior to the event so that we have time to insure you have proper UM credentials for the workshop. This allows enough time for you to get your account adjusted by ITS in case you do not have access to the Linux systems.
URL:https://micde.umich.edu/event/introduction-to-the-linux-command-line-8/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:High Performance Computing,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190917T140000
DTEND;TZID=America/Detroit:20190917T160000
DTSTAMP:20260605T225313
CREATED:20230905T171404Z
LAST-MODIFIED:20230905T171404Z
UID:10000266-1568728800-1568736000@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/introduction-to-deep-neural-networks-with-keras-tensorflow-4/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
END:VEVENT
END:VCALENDAR