We welcome you to our new platform! In this page you will learn:
- what Spider is all about
- whether it is suitable for your research project
- what are the collaboration options
- how to obtain access and work within a Spider project
1.1. Spider at a glance¶
Spider is a versatile high-throughput data-processing platform aimed at processing large structured data sets. It runs on top of our in-house elastic Cloud. This allows for processing on Spider to scale from many terabytes to even petabytes. Utilizing many hundreds of cores simultaneously Spider can process these datasets in exceedingly short timespans. Superb network throughput ensures connectivity to external data storage systems.
Apart from scaling and capacity, Spider is aimed at interoperability with other platforms. This interoperability allows for a high degree of integration and customization into the user domain. Spider is further enhanced by specific features supporting collaboration, data (re)distribution, private resources or even private Spider instances.
Have a glance here of the main features offered by Spider:
1.2. Platform components¶
Spider is a feature-rich platform under continuous development. We keep adding new features to the platform in order to meet the needs of researcher projects working with massive datasets.
Spider is built on powerful infrastructure and designed with the following components:
- Batch processing cluster (based on Slurm) for generic data processing applications
- Batch partitions to enable Single-core, Multi-core, Whole-node, High-memory and Long-running jobs
- Large CephFs data staging area (POSIX-compliant filesystem) scales to PBs without loss of performance or stability
- Large and fast scratch area’s (NVMe SSDs) on the worker nodes
- Fast network uplink (1200 Gbit/s) allowing for scalable parallel data transfers from other SURFsara based storage systems (e.g. dCache, SWIFT), or from external storage systems
- Role-based project spaces tailored for data-centric projects
- Scientific catalogs for cross-project collaboration
- Web access over HTTPS for public data distribution and sharing with external collaborators
- Singularity containers for software portability
- CVMFS/Softdrive support for software distribution
- Jupyter Notebooks
- Interactive jobs and direct visualization from within jobs
- Specific tooling for data-processing workflows
- Workflow management support
- Diverse authentication methods
- Private resources for special purposes (reservations, private nodes, private clusters)
1.3. Best suited cases¶
The best-suited cases for Spider are scientific projects with a requirement to process relatively large data sets. For example research projects suitable for Spider that deal with massive datasets are commonly in: Genomics, Proteomics, Earth observation, Astronomical observation, Climate modeling, Engineering or Physics experiments.
You would be eligible for Spider if your project reflects some of the following needs:
- Processing of large amount of data of many terabytes to petabytes in short time spans
- Processing of large amount of independent simulations and workflows
- Interactive processing with user-friendly interfaces for efficient data handling
- Industry standard interfaces and other interoperability features
- Co-working with your collaborators on the same project-based workspace
- Accessing external storage facilities with fast connectivity
Also Spider is a viable alternative for current and potential Grid users who are looking to use a more customizable system. It is a low-threshold platform, as opposed to highly complex Grid platforms that take many months of specialist development before they can start. Being built upon the exact same physical data-processing infrastructure and sharing the same scalable network connectivity as the Grid-based processing environments, Spider offers the same data-parallel processing capabilities as the most powerful Grid platforms.
Note though that while it’s great for data-intensive applications, Spider is not really aimed at:
- HPC applications where operations per second are critical
- Processing of simulations that require multi-node execution
- Applications that cannot be ported onto Linux-based system
Spider is designed for Big Science which requires collaboration. Spider supports several ways to collaborate, either within your project, across projects, or to external sources.
1.4.1. Project space¶
Project spaces on Spider are shared workspaces given to team members that enable collaboration through sharing data, software and workflows. Within your project space there are four folders:
- Data: Housing source data from data managers
- Share: For sharing between project members
- Public: For sharing publicly through webviews
- Software: Scripts, libraries and tools
Spider enables collaboration for your project with granular access control to your project space through project roles, enabling collaboration for any team structure:
- data manager role: designated data dissemination manager; responsible for the management of project-owned data
- software manager role: designated software manager; responsible to install and maintain the project-owned software
- normal user role: scientific users who focus on their data analysis
1.4.2. Scientific catalog¶
Collaboration is also possible across different Spider projects. These are cases where different user groups work on projects with different scope and goals but need to (partly) share read-only data (such as observations or biobank data). Spider offers a place for multiple project teams to collaborate by sharing data sets or tools. This workspace is called scientific catalog and it is not offered by default to a project.
The scientific catalog data can be either open to everyone on the platform or private to selected Spider project groups.
The scientific catalog has only one (but important) role:
- scientific catalog manager: designated data dissemination SC manager; responsible for populating the catalog and deciding which Spider project groups have read access to that catalog.
1.4.3. Interoperability hotspot¶
In contrast to many of the processing platforms already available, typically offering an all-inclusive solution within the boundaries of the their environment, Spider is exactly the opposite. It aims to be a connecting platform in a world that has already a lot to offer in terms of storage systems, data distribution and collaboration frameworks, software management and portability systems, and pilot job and task management frameworks. The Spider platform can hook them all together as an interoperability hotspot to support a variety of data processing and data collaboration use cases.
For all external services supported, even services owned by the users themselves, Spider offers optimized configurations and practical guidelines how to connect to these services together into a practical processing environment tailored specifically to each project.
1.5. Project lifecycle¶
If you decided that Spider sounds suitable for your research project, then you can apply to obtain access and start your project or join an existing one.
1.5.1. Starting a project¶
For information about the granting routes on Spider please see our Proposals Page.
Before applying for a new project on Spider we suggest you to contact our helpdesk to discuss your project.
1.5.2. Extending a project¶
1.5.3. Joining an existing project¶
If you are interested to join an existing project please contact our our helpdesk. Upon your request we will verify with the project PI whether we can give you access to the project and what your project role would be.