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.
Instructor: Theodore Hall, U-M 3D Lab, The Duderstadt Center
Space is limited. Register here.
Beginning in January of 2019, most of CSCAR’s workshops will be offered free of charge to UM students, faculty, and staff.
CSCAR is able to do this thanks to funding from UM’s Data Science Initiative. Registration for CSCAR workshops is still required, and seats are limited.
CSCAR requests that participants please cancel their registration if they decide not to attend a workshop for which they have previously registered.
Note that a small number of workshops hosted by CSCAR but taught by non-CSCAR personnel will continue to have a fee, and fees will continue to apply for people who are not UM students, faculty or staff.
A series of training workshops in high performance computing will be held Feb. 12 through March 6, 2018, presented by CSCAR in conjunction with Advanced Research Computing – Technology Services (ARC-TS).
Introduction to the Linux command Line
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 known as the “command line.”
Location: East Hall, Room B254, 530 Church St.
Dates: (Please sign up for only one)
• Tuesday, Feb. 13, 1 – 4 p.m. (full description | registration)
• Friday, Feb. 16, 9 a.m. – noon (full description | registration)
Introduction to the Flux cluster and batch computing
This workshop will provide a brief overview of the components of the Flux cluster, including the resource manager and scheduler, and will offer students hands-on experience.
Location: East Hall, Room B254, 530 Church St.
Dates: (Please sign up for only one)
• Monday, Feb. 19, 1 – 4 p.m. (full description | registration)
• Tuesday, March 6, 1 – 4 p.m. (full description | registration)
Advanced batch computing on the Flux cluster
This course will cover advanced areas of cluster computing on the Flux cluster, including common parallel programming models, dependent and array scheduling, and a brief introduction to scientific computing with Python, among other topics.
Location: East Hall, Room B250, 530 Church St.
Dates: (Please sign up for only one)
• Wednesday, Feb. 21, 1 – 5 p.m. (full description | registration)
• Friday, Feb. 23, 1 – 5 p.m. (full description | registration)
Hadoop and Spark workshop
Learn how to process large amounts (up to terabytes) of data using SQL and/or simple programming models available in Python, R, Scala, and Java.
Location: East Hall, Room B250, 530 Church St.
Dates: (Please sign up for only one)
• Thursday, Feb. 22, 1 – 5 p.m. (full description | registration)
A few seats are still available in the following ARC-sponsored training workshops. Please click on the course titles for more information and to register. All sessions take place in Room B743, East Hall.
HPC 101: High Performance Computing Workshop
Monday, Feb. 9, 1 – 5 p.m.
Wednesday, Feb. 11, 1 – 5 p.m.
Prerequisite: HPC 100 or equivalent
This course will provide an overview of cluster computing in general and how to use the U-M Flux Cluster in particular. Topics to be covered include cluster computing concepts, common parallel programming models, introduction to the Flux Cluster; creating, submitting, observing, and analyzing cluster jobs; common pitfalls and how to avoid them; and some useful tools. We will issue you a temporary allocation to use for the course, or you can use your existing Flux allocations, if any. Short sample programs will be provided, or come to class with your own.
HPC 201: Advanced High Performance Computing Workshop
Friday, Feb. 13, 1 – 5 p.m.
Monday, Feb. 16, 1 – 5 p.m.
Prerequisites: HPC 101 or equivalent
This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob, qstat, and other tools; use of common scientific applications including Python, MATLAB, and R in parallel environments; parallel debugging and profiling of C and Fortran code, including logging, gdb (line-oriented debugging), ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs; and an introduction to using GPUs.
The Center for Statistical Consultation and Research is offering several workshops this term, including sessions on SPSS, Applied Survival Analysis, Data Management and Macros with SPSS, SAS, R, Stata, and Regression Analysis.
A complete schedule can be found on CSCAR’s Workshops web page.
More information about CSCAR’s services are available on its home page.
Registration is open for a series of ARC-sponsored training courses and workshops in high performance computing in January and February. Each session — beginning, intermediate and advanced — will be offered three times.
HPC100 — Introduction to the Linux Command Line for HPC
1 – 4 p.m., B743 East Hall
Thursday, January 22
Monday, February 2
Friday, February 4
This course will familiarize students with the basics of accessing and interacting with high-performance computers using the GNU/Linux operating system’s command line. For more information, and to register, visit this page.
HPC101 — High Performance Computing Workshop
1 – 5 p.m., B743 East Hall
Tuesday, February 3
Monday, February 9
Wednesday, February 11
This course provides an overview of cluster computing in general and how to use the Flux cluster in particular. (Prerequisite: HPC 100 or equivalent.)
For more information, and to register, visit this page.
HPC201 — Advanced High Performance Computing Workshop
1 – 5 p.m., B743 East Hall
Thursday, February 5
Friday, February 13
Monday, February 16
This course will cover some more advanced topics in cluster computing on the U-M Flux Cluster. Topics to be covered include a review of common parallel programming models and basic use of Flux; dependent and array scheduling; advanced troubleshooting and analysis using checkjob, qstat, and other tools; use of common scientific applications including Python, MATLAB, and R in parallel environments; parallel debugging and profiling of C and Fortran code, including logging, gdb (line-oriented debugging), ddt (GUI-based debugging) and map (GUI-based profiling) of MPI and OpenMP programs; and an introduction to using GPUs. (Prerequisite: HPC101 or equivalent.)
For more information, and to register, visit this page.
