Aalto Scientific Computing¶
This site contains documentation about scientific and data-intensive computing at Aalto University and beyond. It is targeted towards Aalto researchers, but has some useful information for everyone.
15/12/2022 Follow us on Mastodon.
21/10/2022 Upgrade of the triton login node: After running out of memory several times on our login node, we upgraded the memory from previously 128Gb to 256Gb. This is hopefully sufficient for most compilation and development work happening on the node. Any computation or memory intensive job should still be run on the compute nodes, but this upgrade provides us with a more robust system.
From 22nd till 25th of November we will be running our popular *Python for Scientific Computing* course again. The registration is open and can be accessed here. Please also visit our training webpages to check other upcoming courses or request a re-run of past hands-on courses.
The Aalto environment¶
Aalto provides a wide variety of support for scientific computing. For a summary, see the IT Services for Research page. For information about data storage at Aalto, see the section on data management below.
- Aalto tools
- Aalto account
- Aalto Linux
- Aalto Mac
- Aalto Windows
- Data storage
- Data: outline, requesting space, requesting access
- Science-IT data policy
- Remote Access
- Remote Jupyter Notebook on shell servers
- Paniikki: Computer Lab For Students
- Aalto Gitlab
- Open Source at Aalto
- Standalone Matlab
In this section, you can find some information and instructions on data management. Concrete information: main Aalto services and global services. Main Theoretical information: Aalto-specific summary and Aalto’s Research Data Management pages.
Triton is the Aalto high performance computing cluster. It is your go-to resources for anything that exceeds your desktop computer’s capacity. To get started, you could check out the tutorials (going through all the principles) or quickstart guide (if you pretty much know the basics).
Aalto Research Software Engineers¶
Skills to do science are different than skills to write good research code. The Aalto Research Software Engineers (AaltoRSE) provide support and mentoring to those using computing and data so that everyone can do the best possible work.
In this section, you find general (not Aalto specific) scientific computing resources. We encourage other sites to use and contribute to this information.
- Scientific computing tips
- Encryption for researchers
- Git-annex for data management
- Hybrid events
- Pitfalls of Jupyter Notebooks
- nbscript: run notebooks as scripts
- New group leaders: what to know about computational research
- Package your software well
- Linux shell crash course
- The Zen of Scientific computing
- Practical git PRs for small teams
We have various recommended training courses for researchers who deal with computation and data. These courses are selected by researchers, for researchers and grouped by level of skill needed.
Don’t go alone, we are there! There is all kinds of “folk knowledge” to efficiently use the tools of scientific computing, and we would like to learn that. In particular, our community is welcome to come to our SciComp garage even for small random chats about your work, but there are plenty of other ways to ask for help, too.
Aalto Scientific Computing isn’t a HPC center - we provide HPC services, but our goal is to support scientific computing no matter what resources you need. Computing is hard, and we know that support is even more important than the infrastructure. If you are a unit at Aalto University, you can join us. [Mastodon, Twitter]
Aalto Scientific Computing (ASC) maintains these pages with the help of the Aalto community. This site is open source: all content is licensed under CC-BY 4.0 and all examples under CC0 (public domain). Additionally, this is an open project and we strongly encourage anyone to contribute. For information, see the About this site and the Github links at the top of every page. Either make Github issues, pull requests, or ask for direct commit access. Be bold: the biggest problem is missing information, and mistakes can always be fixed.Mastodon