High Performance Computing
Current facets (Pre-Master)
Erasmus University Rotterdam provides its faculty with advanced computing power to facilitate work on data with EUR colleagues as well as with colleagues from other universities. This service, the SURFsara High Performance Computing Services, meet the professional needs of running large jobs or many jobs on a computer.
If your task:
- would take months/years on a normal PC
- requires more space (memory/storage) than available in your PC
you will probably benefit by using a HPC service.
How to access
After EUR approval:
What do I get
1. The Lisa system
The Lisa system is a cluster computer consisting of several hundreds of multi-core nodes running the Linux operating system. The system is installed and maintained by SURFsara.
Research Capacity Computing Services (RCCS)
The Lisa system is used for the SURFsara service Research Capacity Computing Services (RCCS). RCCS is a SURFsara compute service for researchers coping with many large computational tasks. RCCS covers computing tasks which are typically characterized by a large amount of independent, moderately parallel, computing tasks. The tasks itself can be run in parallel on the computing system. RCCS is typically for those compute tasks which in practice cannot be run on either departmental or university computing systems, due to their size.
2. Cartesius: the Dutch supercomputer
Cartesius is the Dutch national supercomputer. Cartesius is a general purpose capability system and is designed to be a well balanced system. If you need one or more of: many cores, large SMP nodes, much memory, a fast interconnect, a lot of disk storage, or a fast I/O subsystem, Cartesius is the machine of choice.
3. HPC cloud
With the HPC Cloud facility, SURFsara offers self-service, dynamically scalable and fully configurable HPC systems to the Dutch academic community. Users have, for example, a free choice of operating system and software.
The HPC Cloud offers full control over a HPC cluster, with fast CPUs and high memory nodes and it is possible to attach terabytes of local storage to a compute node. Because of this flexibility, users can fully tailor the system for a particular application. Long-running and small compute jobs are equally welcome. Additionally, the system facilitates collaboration: users can share control over their virtual private HPC cluster with other users and share processing time, data and results. A portal with wiki, fora, repositories, issue system, etc. is offered for collaboration projects as well.
4. Data Archive Description
Data ingested to the Data Archive of SURFsara is kept in two different tape libraries located at two different locations in the Netherlands. The Data Archive is connected with our compute infrastructure via a fast network connection allowing fast staging of archived data. Users are given a login, which enables immediate, 24/7 access to the service.
4.1. The Data Archive supports:
Long-term and safe preservation of data.
High-level support concerning the optimal use of the service.
Data access is facilitated by several data transfer protocols that can be employed in a Linux or Windows environment:
Via internet, using SSH, (HPN)SCP, SFTP, rsync, GridFTP;
Via iRODS federations that allow implementation and execution of user-defined data policies. Currently, the EUDAT-B2SAFE policies are available.
4.2. Data Ingest Service
The Data Ingest Service offers users the possibility to upload data from external storage media such as external hard-drives to the Data Archive storage facilities. The service is suitable if there is not enough bandwidth to transfer data via internet. Refer to the Data Ingest Service page for an extensive description.
4.3. PID Services
Persistent Identifiers (PIDs) are used to make data referable in papers and traceable across different infrastructures. SURFsara offers the possibility to attach EPIC PIDs to data ingested in the Data Archive. More info can be found on the PID consortium website.
See for experiences by EUR researchers with HPC: Easy access to processing power for computational recommendation models by dr. Flavius Frasincar [ERIM].
See also the introductory video on the SURFsara compute services: Cartesius, LISA, HPC
For support, (also for choosing the right HPC service for you) please contact: firstname.lastname@example.org
Phone: +31 10 4088006
See also the SURFsara Tutorials