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EGI Workload manager (also known as DIRAC4EGI) is a service is provided to the EGI community as a workload management service used to distribute the users' computing tasks among the available resources both HTC and cloud.
|Tool name||Workload Manager|
|Tool Category and description||A workload management service used to distribute the users' computing tasks among the available resources both HTC and cloud.|
|email@example.com, firstname.lastname@example.org, email@example.com (operation team)|
|GGUS Support unit||DIRAC|
|GOC DB entry||GRIDOPS-DIRAC4EGI|
|Requirements tracking - EGI tracker||technical-support-cases, dirac4egi-eiscat3d-requirements, dirac4egi-mobrain-requirements|
|Issue tracking - Developers tracker||https://github.com/DIRACGrid/DIRAC/issues|
|Test instance url||https://dirac.egi.eu/|
|License||GNU General Public License v3.0|
Workload Manager provides a Workload Management Service (WMS) for High Throughput Computing resources based on DIRAC, which improves the general job throughput compared with native management of grid computing resources. Cloud computing resources are managed as well in a uniform and transparent way for the users.
- Workload Manager configuration allows to choose appropriately computing and storage resources maximising their usage efficiency for particular user requirements.
- All the Workload Manager functionality is accessible through friendly user interfaces, including a Web Portal. It has an open architecture and allows easy extensions for the needs of particular applications.
DIRAC data and job management systems ensure proven production scalability up to peaks of more than 100 thousand concurrently running jobs for the LHCb experiment. This is by far large enough for the computing requirements of environmental science in a sensible temporal horizon.
Targeting User Groups
The service suits for the established Virtual Organization communities, long tail of users, SMEs and Industry
- EGI and EGI Federation participants
- Research communities
This service platform eases scientific computing by overlaying distributed computing resources in a transparent manner to the end-user. For example, WeNMR, a structured biology community, uses DIRAC for a number of community services, and reported an improvement from previous 70% to 99% with DIRAC job submission. The benefits of using this service include but not limited to :
- Maximize usage efficiency by choosing appropriately computing and storage resources on real-time
- Large–scale distributed environment to manage and handle data storage, movement, accessing and processing
- Handle job submission and workload distribution in a transparent way
- Interoperable, handle different storage supporting both cloud and grid capacity
- User-friendly interface that allows to choose among different DIRAC services
Technical Service Architecture
DIRAC was originally developed to support the production activities of the LHCb experiment at CERN (~10 years ago), today it acts as is a general purpose software support for Grid, Cloud, HPC, targeting various large scientific communities including LHCb, Belle II, EGI, CTA, GridPP, WeNMR, VIP, FranceGrilles, SKA, VIRGO, etc. DIRAC provides complete solutions for production managements, handling distributed large scale of scientific data and optimising job executions.
The DIRAC framework offers standards rules to create DIRAC extension, large part of the functionality is implemented as plugins and it allows to customize the DIRAC functionality for a particular application with minimal effort. It provides multiple commands usable in a Unix shell giving access to all the DIRAC functionalities. It also provides a RESTful API suitable for use with application portals (e.g. WS-PGRADE portal is interfaced with DIRAC this way) and a Python programming interface is the basic way to access all the DIRAC facilities and to create new extensions. For all DIRAC service please check it out at DIRAC documentation
The Workload Manager service (DIRAC4EGI) is a cluster of DIRAC service running on EGI resources (HTC, CLOUD, HPC) supporting multi-VO. The main service components include:
- Workload Management System (WMS) architecture is composed of multiple loosely coupled components working together in a collaborative manner with the help of a common Configuration Services ensuring reliable service discovery functionality. Modular architecture allows to easily incorporate new types of computing resources as well as new task scheduling algorithms in response to evolving user requirements. DIRAC services can run on multiple geographically distributed servers which increases the overall reliability and excellent scalability properties.
- REST server providing language neutral interface to DIRAC service
- Web portal provides simple and intuitive access to most of the DIRAC functionalities including management of computing tasks and distributed data. It also has a modular architecture designed specially to allow easy extension for the needs of particular applications.
and all DIRAC service are at or above TRL8
The modular organiszation of the DIRAC components allows selecting a subset of the functionality suitable for particular applications or easily adding the missing functionality. These are very useful for communities to have a customised environments to handling own data.
- Requests for service:
1. Submit a service request via the EGI website/marketplace request form 2. The UCST team contacts CNRS to request the support the service integration (on-boarding of the new customer)
The EGI Workload Manager is already used in production by some early adopters like WeNMR, that was able to easily switch their Science Gateways from gLite WMS to DIRAC. http://indico3.twgrid.org/indico/getFile.py/access?contribId=61&sessionId=20&resId=0&materialId=slides&confId=593. Ongoing development (by Jun 2018) is supported by the WeNMR Thematic Service under the EOSC-hub umbrella.
EISCAT and EGI set up a Competence Centre (CC) in the context of the EGI-Engage project to provide researchers with data analysis tools to improve their scientific discovery opportunities.
The team developed a web portal for researchers to to discover, access and analyse the data generated by EISCAT_3D. The CC opted to use the EGI Workload Manager service.
The service provides a web-based graphical interface and command line interface to interact with data search and job management. The system also facilitates the development of data models and modelling tools within the EISCAT_3D community, and the applicability of operating a central portal service for scientists to interact and compute with EISCAT data. https://wiki.egi.eu/wiki/Competence_centre_EISCAT_3D#First_portal_-_proof_of_concept
New development (by Jun 2018) is supported by the EISCAT-3D CC under the EOSC-hub umbrella.
Virgo is a giant laser interferometer designed to detect gravitational waves and located at the European Gravitational Observatory (EGO) site in Cascina, a small town near Pisa. Virgo was designed and built by a collaboration between the French National Center for Scientific Research (CNRS) and the National Institute for Nuclear Physics (INFN). It is now operated and improved by an international collaboration of scientists from France, Italy, the Netherlands, Poland, and Hungary. In 2017, the Virgo and LIGO Scientific Collaborations received the Physics Nobel Prize for their role in the detection of gravitational waves.
Virgo is now performing tests using the EGI workload manager service. The fact that DIRAC is already used by many communities as a mature tool was an important factor in making this decision. In addition to the EGI Workload Manager, the Virgo collaboration also decided to test distributed data management solution to better understand its potential. Considering the Data Management needs of Virgo, it was agreed to set-up a dedicated DIRAC file catalog component as well, hosted at the INFN data centre in Bologna, Italy.
The tests conducted so far (by Jun 2018) showed good performance results. For example, the catalog was populated with millions of records, and the performances were good even with a large number of records similar to the real numbers that are expected to be in production. The tests also allowed to find and fix some misconfigurations on the resource centres currently available in France, Italy, and the Netherlands. In the following months, more sites will be involved and there are plans to move and register the production data between the sites, using the DIRAC data transfer feature.
- DIRAC documentation: http://dirac.readthedocs.io/en/latest/
- DIRAC gitHub source: https://github.com/DIRACGrid
- DIRAC Virtual Research Environment pilot for EGI workshop, https://indico.egi.eu/indico/event/1994/session/19/#20140522
- DIRAC4EGI webinar 2016: https://indico.egi.eu/indico/event/2978/
- DIRAC4EGI presentation at the 6th DIRAC User Workshop 2016 : https://indico.cern.ch/event/477578/contributions/2168291/
- DIRAC4EGI presentation at the 7th DIRAC User Workshop 2017: https://indico.cern.ch/event/609507/contributions/2577162/
- DIRAC4EGI presentation at the 8th DIRAC User Workshop 2018: https://indico.cern.ch/event/676817/contributions/2770700/