1. LIT participation LIT participation Ivanov V.V. Laboratory of Information Technologies Meeting on proposal of the setup preparation for external beams of the Nuclotrom-M. February 4, 2011, LHEP, Dubna February 4, 2011, LHEP, Dubna

2. Information, computer and network support of JINR's activity 20 Gb/s 1. Telecommunication channels: 1. Telecommunication channels: Moscow M9 - 20 Gb/s; CERN – 10 Gb/s; RBnet - 10 Gb/s; RASnet - 10 Gb/s; RadioMSU - 10 Gb/s; GEANT – 12.4 Gb/s; GLORIAD - 1 Gb/s. 2. JINR Local area network: ~ 7000 computers and nodes, Users – 3726, IP – 8300, Remote VPN users – 1310, High-speed transport – up to 10 Gb/s. Distribution of the incoming and outgoing JINR traffic since 2003 Network monitoring information system - more than 350 network nodes are in round-the-clock monitoring

3. JINR Central Information and Computing Complex (CICC) CICC comprises 1104 CPU Total performance 2800 kSI2K Disk storage capacity 1068 TB 20112012-2013 CPU (kSI2k)35005000 Disk systems (TB)15002500 Mass storage (TB)-1000 Estimates of the JINR CICC resources increase in the future Performance Growth of the JINR CICC resources in 2003 - 2010 The distribution of batch jobs over the Institute’s subdivisions and user groups excluding the grid in 2010 ~ 600 CPU will be added during next few months

4. JINR Grid Infrastructure The CPU time monitoring in the year 2010 places the JINR grid- site on the 10-th place among the 163 Tier2 sites of WLCG. It covers about 40% of the RDIG share to the LHC. Тор 12 WLCG-Tier2 sites (June 2009 – December 2010) WLCG - Tier-2 site Normalised CPU time US-AGLT2 (USA) 63,817,300 FR-GRIF (France) 38,633,307 US-MWT2_UC (USA) 32,100,167 DE-DESY-HH (Germany) 30,815,991 FR-IN2P3-CC-T2 (France) FR-IN2P3-CC-T2 (France) 29,178,055 US-WT2 (USA) 27,544,510 UKI-SCOTGRID- GLASGOW (UK) 23,655,140 JINR-LCG2 22,203,264 (USA) T2_US_UCSD (USA) 21,120,768 (USA) GLOW (USA) 20,435,703 (USA) Nebraska (USA) 19,952,399 CYFRONET-LCG2 (Poland) 19,470,897

5. CBM(GSI) - Development of Methods and Algorithms for Global Tracking TASK: Development of methods, algorithms and codes for global tracking in STS, RICH and TRD ­ track matching; Kalman filter for track fitting; Further development of pattern recognition and ring reconstruction algorithms for RICH; Development and comparative study of different algorithms for accurate momenta reconstruction; Development of algorithms for accurate reconstruction and selection of primary and secondary vertexes; Magnetic field calculations; GEANT simulations. Modern technologies for parallelization: 1)Vectorization (SIMD - Single Instruction Multiple Data) 2)Multithreading (many cores CPU) Fast parallel algorithms were developed for event reconstruction in the CBM Event reconstruction algorithms: 1)Tracking: Kalman filter and track following 2)Ring reconstruction: Hough Transform Two PhD thesis were delivered on the basis of these studies Results: 1)High track and ring reconstruction efficiency (93-95%) 2)Very fast algorithms Initial Time [ms/event] Parallel Time [ms/event] Speedup Tracking7301.5 487 Ring reconstruction 3752.5 143 December, 2010 - a first data production on the CBMGRID, with LIT and GSI as participating sites. Produced 5,000,000 UrQMD events (35 AGeV Au+Au, min.bias).

6. Ξ -, V0 reconstruction in Au-Au central collisions at 4 AGev kinetic beam energy with CBM Simulation Event reconstruction Detection strategy Cuts on proton, π - and π + tracks Cuts on Λ candidates and K0S candidates parameters Cuts on Ξ - parameters Reconstructed invariant mass distribution of Ξ - candidates Efficiency analysis Significance for Ks z vertex Reconstructed invariant mass distribution of Ξ - candidates Results. A set of cuts for Λ, Ks and Ξ - -barion reconstruction using KFParticle package was obtained. The track and vertex reconstruction software provides good momentum and invariant mass resolution. The study was based on realistic detector geometry. Realistic response from double- sided segmented silicon strip detector was assumed in the simulations. The influence of track multiplicity on the Ξ - -reconstruction efficiency was studied. The reconstruction method allows CBM experiment to collect about 8.83 ·10 3 Ξ - s with signal to background ratio S/B 2σ = 7.83 per 10 9 central events.

8. Thank you for your attention !