We present our results on updating the middleware of Russian GRID sites to be able to continue processing ALICE data in the future, including the HL stage of the Large Hadron Collider operation. We ...will share our experience with one of the GRID sites and discuss some practical cases of scaling the updated middleware to other Russian sites in 2022–2023.
Abstract
CERN experiments are preparing for the HL-LHC era, which will bring an unprecedented volume of scientific data. These data will need to be stored and processed by thousands of physicists, ...but expected resource growth is nowhere near the extrapolated requirements of existing models, in terms of both storage volume and compute power. Opportunistic CPU resources such as HPCs and university clusters can provide extra CPU cycles, but there is no opportunistic storage. In this article, we will present the main architectural ideas, deployment details, and test results, with emphasis on our research to build a prototype of a distributed data processing and storage system with a focus on optimizing the efficiency of resources by reducing overhead costs for accessing the data. The described prototype was built using the geographically distributed WLCG sites and university clusters in Russia.
In this contribution we discuss the various aspects of the computing resource needs experiments in High Energy and Nuclear Physics, in particular at the Large Hadron Collider. This will evolve in the ...future when moving from LHC to HL-LHC in ten years from now, when the already exascale levels of data we are processing could increase by a further order of magnitude. The distributed computing environment has been a great success and the inclusion of new super-computing facilities, cloud computing and volunteering computing for the future is a big challenge, which we are successfully mastering with a considerable contribution from many super-computing centres around the world, academic and commercial cloud providers. We also discuss R&D computing projects started recently in National Research Center ``Kurchatov Institute''
The next phase of LHC Operations - High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start ...operation in 2027-2028 and will deliver an unprecedented scientific data volume of multi-exabyte scale. This amount of data has to be stored and the corresponding storage system should ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data processing model will not be able to provide the required infrastructure growth even taking into account the expected hardware technology evolution. To address this challenge the new state-of-the-art computing infrastructure technologies are now being developed and are presented here. The possibilities of application of the HL-LHC distributed data handling technique for other particle and astro-particle physics experiments dealing with large-scale data volumes like DUNE, LSST, Belle-II, JUNO, SKAO etc. are also discussed.
Rapid increase of data volume from the experiments running at the Large Hadron Collider (LHC) prompted physics computing community to evaluate new data handling and processing solutions. Russian grid ...sites and universities' clusters scattered over a large area aim at the task of uniting their resources for future productive work, at the same time giving an opportunity to support large physics collaborations. In our project we address the fundamental problem of designing a computing architecture to integrate distributed storage resources for LHC experiments and other data-intensive science applications and to provide access to data from heterogeneous computing facilities. Studies include development and implementation of federated data storage prototype for Worldwide LHC Computing Grid (WLCG) centres of different levels and University clusters within one National Cloud. The prototype is based on computing resources located in Moscow, Dubna, Saint Petersburg, Gatchina and Geneva. This project intends to implement a federated distributed storage for all kind of operations such as read/write/transfer and access via WAN from Grid centres, university clusters, supercomputers, academic and commercial clouds. The efficiency and performance of the system are demonstrated using synthetic and experiment-specific tests including real data processing and analysis workflows from ATLAS and ALICE experiments, as well as compute-intensive bioinformatics applications (PALEOMIX) running on supercomputers. We present topology and architecture of the designed system, report performance and statistics for different access patterns and show how federated data storage can be used efficiently by physicists and biologists. We also describe how sharing data on a widely distributed storage system can lead to a new computing model and reformations of computing style, for instance how bioinformatics program running on supercomputers can read/write data from the federated storage.
The Large Hadron Collider (LHC)' operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the ...fundamental nature of matter and the basic forces that shape our universe. Computing models for the High Luminosity LHC era anticipate a growth of storage needs of at least orders of magnitude; it will require new approaches in data storage organization and data handling. In our project we address the fundamental problem of designing of architecture to integrate a distributed heterogeneous disk resources for LHC experiments and other data- intensive science applications and to provide access to data from heterogeneous computing facilities. We have prototyped a federated storage for Russian T1 and T2 centers located in Moscow, St.-Petersburg and Gatchina, as well as Russian CERN federation. We have conducted extensive tests of underlying network infrastructure and storage endpoints with synthetic performance measurement tools as well as with HENP-specific workloads, including the ones running on supercomputing platform, cloud computing and Grid for ALICE and ATLAS experiments. We will present our current accomplishments with running LHC data analysis remotely and locally to demonstrate our ability to efficiently use federated data storage experiment wide within National Academic facilities for High Energy and Nuclear Physics as well as for other data-intensive science applications, such as bio-informatics.
In this paper we present first results on the use of Polar WRF model for regionalization of the atmospheric circulation in the Arctic region produced by the global climate model INM-CM48 developed in ...INM RAS. We demonstrate that Polar WRF does not show run off effects in the first year of integration, gives reasonable results with respect to the global model with more details in the regions of complex topography and coast line.
Scalable cloud without dedicated storage Batkovich, D V; Kompaniets, M V; Zarochentsev, A K
Journal of physics. Conference series,
05/2015, Letnik:
608, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We present a prototype of a scalable computing cloud. It is intended to be deployed on the basis of a cluster without the separate dedicated storage. The dedicated storage is replaced by the ...distributed software storage. In addition, all cluster nodes are used both as computing nodes and as storage nodes. This solution increases utilization of the cluster resources as well as improves fault tolerance and performance of the distributed storage. Another advantage of this solution is high scalability with a relatively low initial and maintenance cost. The solution is built on the basis of the open source components like OpenStack, CEPH, etc.
ALICE computing update before start of RUN2 Zarochentsev, A. K.; Stiforov, G. G.
Kompʹûternye issledovaniâ i modelirovanie (Online),
6/2015, Letnik:
7, Številka:
3
Journal Article
Recenzirano
Odprti dostop
The report presents a number of news and updates of the ALICE computing for RUN2 and RUN3. This includes: - implementation in production of a new system EOS; - migration to the file system CVMFS to ...be used for storage of the software; - the plan for solving the problem of "Long-Term Data Preservation"; - overview of the concept of "O square", combining offline and online data processing; - overview of the existing models to use the virtual clouds for ALICE data processing. Innovations are shown on the example of the Russian sites.
On the threshold of LHC data there were intensive test and upgrade of GRID application software for all LHC experiments at the top of the modern LCG middleware (gLite). The update of such software ...for ALICE experiment at LHC, AliEn1 had provided stable and secure operation of sites developing LHC data. The activity of Russian RDIG (Russian Data Intensive GRID) computer federation which is the distributed Tier-2 centre are devoted to simulation and analysis of LHC data in accordance with the ALICE computing model 2. Eight sites of this federation interesting in ALICE activity upgrade their middle ware in accordance with requirements of ALICE computing what ensured success of MC production and end-user analysis activity at all eight sites. The result of occupancy and efficiency of each site in the time of LHC operation will be presented in the report. The outline the results of CPU and disk space usage at RDIG sites for the data simulation and analysis of first LHC data from the exposition of ALICE detector 3 will be presented as well. There will be presented also the information about usage of parallel analysis facility based on PROOF 4.
PDF
