ICT and the Social Sciences Research Laboratories are pleased to set up new services for using NVivo.
NVivo is a tool to support qualitative analysis. NVivo is an example of Computer-assisted qualitative data analysis software. What qualitative research is.
ICT is pleased to partner with the Social Sciences Research Laboratories (SSRL) in order to provide better service for researchers doing qualitative analysis.
A number of related NVivo services are available:
- Consulting, data coding and data analysis capacity are available through the SSRL
- Subsidized prices for NVivo client licenses are available through the Campus Computer Store
- Standard or customized NVivo training may be arranged through the SSRL
- ICT provides access to a shared implementation of the NVivo Server software which can support a number of research projects. NVivo Server supports multi-user, concurrent access to an NVivo database.
- Additionally, a remote access service supports off-campus access to the NVivo Server
- ICT manages the relationship with vendor QSR International
In order to access the service:
- The licensing for NVivo restricts it to non-commercial use associated with the University.
- Setups for NVivo Server will be made for Principal Investigators of research projects.
- Each user of the NVivo Server software needs an NSID
The current version of MATLAB, R2015a or 8.5, depending on the versioning system you prefer, is now available for installation on campus. Continue reading
The current version of Maple (Maple 2015) is now available on campus. This version has a number of new features. There are improvements in the graphical features, data handling, and there is support for handling units (temperature in Kelvin, Celsius and Fahrenheit as an example).
UPDATE: MapleSoft has just announced webinars on learning Maple 2015.
Please contact Research Computing for information on installing and using Maple.
The latest version of COMSOL, 5.0 is now available through the campus license distribution. Continue reading
Qualitative Analysis is an important part of many research projects that involve interviews or qualitative surveys. ICT is in the final stages of launching a new service to support qualitative research at the University of Saskatchewan. Continue reading
We’d like to bring the ownCloud service to the attention of the research community. It is an exciting new feature that is part of the data storage suite that ICT offers to campus. Continue reading
MathWorks has informed us that they have found and resolved a number of problems in MATLAB R2014b that could lead to files being removed.
Information about the bugs and patch is available in bug report #1184018 on MathWorks’ website. In short, the most serious one is removal of files in the current directory when MATLAB exits. The others are crashes when using Simulink. The fixes are ZIP files that must be extracted in the MATLAB R2041b install directory, by a privileged user.
The main distribution from MathWorks has been patched, and installs from the ditto distribution site after the morning of January 16 will have these patches in place.
If you have any questions about these MATLAB patches, please contact Research Computing for answers. Remember to backup your files (such as the .m files) to prevent loss of data or work.
ESRI Canada has given a scholarship to University of Saskatchewan students for the past several years. You can see previous winners on The Spatial Initiative (TSI) web site. They are offering this scholarship again this year. Details of the scholarship are available at the ESRI Canada website. (PDF file) Applications for the scholarship are to be sent via email to GIServices@usask.ca. The deadline for application is January 24, 2015.
Applicants must have a “B+” average in their classes (i.e. a minimum 75% average), and must include a CV and a transcript. They should also note how they have used ESRI software in the past. Other information required follows below: Continue reading
Wolfram Mathematica 10.0.2 is available for install on campus computers. Users are encouraged to try the new version. Continue reading
High performance computing (HPC) is taking a fundamental role in scientific research around the world. Here at the University of Saskatchewan, the research computing group is making efforts to provide access to these new resources and technology to our researchers. As part of these efforts, we designed an delivered an introductory course intended for those graduate students, PDFs and researchers who want to start using HPC resources to speed up their researches.
The first offering of our course ran on September 18 and 19. During 12 hours, the 25 attendees (mostly graduate students and some staff members) reviewed the basic commands and concepts of a Linux system, and the characteristics of the different HPC systems that we have at the University (Plato, Zeno and Meton). They learned how to use efficiently these systems and which kind of problems fit better to each one: shared memory, distributed memory, GPU clusters, and large memory systems. Finally, they analyzed and solved practical examples using the systems (for more details see the course outline below).
Originally we designed the course with an aim to bring new users with no experience or little experience with Linux systems and HPC servers, to a point where they must be able to deploy HPC applications on the most suitable system depending on the problem at hand. The contents of the course could be customized, however, for future offerings according to the attendees backgrounds and interests. We are willing to offer the course again soon, with next offering potentially in January, as long as there are people interested. So, please do not hesitate to contact us at email@example.com with your questions and comments if you are interested in attending.
Original course outline:
1. Introduction to scientific computing
2. Linux basics
3. Compiled and interpreted languages
4. High performance computers
5. Running serial codes in a server
6. Running parallel code in distributed memory systems
7. Running parallel code in shared memory systems
8. Running code with GPU acceleration