Scientific Computing at iDiv
Computers are becoming more essential in research these days to analyze large amounts of data. iDiv provides both the computational resources to face these challenges as well as a high level of support to harness these resources. Therefore, the focus can be placed on research. Assistance can be provided to choose an appropriate platform for research projects and to improve the workflows and adapt them to new challenges, regardless of where these computations are being run – on personal laptops, on terminal servers or on the HPC cluster.
Read up on the scientific computing services to find out how to improve scientific computing workflows with iDiv’s support!
Platforms and Resources
The RStudio servers provide access to the RStudio Web IDE (Integrated Development Environment). There is no installation required and the servers can be accessed from anywhere in the world. This platform is suitable for interactive work and medium-sized computations.
The MS Windows Terminal Servers provide access to applications that run only on Windows, e.g. ArcGIS. Login is possible via RDP (Remoted Desktop Protocol). This platform is suitable for interactive work and medium-sized computations.
The HPC (High-Performance Computing) cluster provides access to virtually all software that runs on Linux. High volumes of jobs can be submitted to the cluster. The cluster scheduler automatically assigns resources to these jobs and processes them over time – no interaction required. This platform allows for the highest degree of automation and is suitable for the largest of computations in all respects of processing power, memory, disk storage and time.
|RStudio Servers||Terminal Servers||HPC Cluster|
|processors||~ 24||~ 50||~ 2,300|
|memory||~ 280GB||~ 600GB||~ 27TB|
|disk storage||~ 5TB||~ 35TB||~ 2.5 Petabyte|
SCaaS – Scientific Computing as a Service
The beginner-friendly scientific computing services can be used, even without knowledge of scientific computing. As ready-to-use data analysis tools are developed, a smooth introduction to scientific computing practices will be provided. During the transition to full autonomy, the scientific computing resources can already be leveraged.
• Requirement analysis
• Sketching workflows
• Developing tools
• Implementing workflows
• Integrating data management
• Providing an issue tracker for ongoing development
• Teaching how to maintain and adapt the tools
The basics of scientific computing are taught in seminars. The acquired knowledge can be advanced as part of the hands-on sessions.
Possible topics include but are not restricted to:
- Introduction to High-Performance Computing
What is high-performance computing?
- Version Control and Collaboration with git
How to manage source code, scripts and papers with the version control system git and how to orchestrate collaboration beyond using comments in MS Word.
- Linux, the Command Line and Shell Scripting
How to use Linux via its flexible and powerful user interface, the command line.
- Reproducible Research
How to create workflows with baked-in reproducibility.
Hands-on sessions are offered to deal with specific topics in depth. The sessions are ideally suited to find solutions to particular problems or to gain knowledge in a specific area of scientific computing.
Possible session topics include but are not limited to:
- Workflow management
Automatic result validation / verification
- Data management
- Project administration
- Performance analysis
- Software design and development