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Computing web : KCMS Computing project


This is the main page of the KCMS computing project.

KCMS Computing workgroup activities:

  • KCMS computing resource management, general planning
  • Share know-hows for computing Tier site operation
  • Support full analysis workflow for KCMS users, provide general user guides
  • Feedback to tier site administartors

From the experiences in LHC-CMS Run I, a powerful computing resource is proven to be the key for the successful physics analysis. During the LS1 period, a task force for the KCMS computing is organised to support efficient computing for the data analysis. In the KCMS, there are 1 official Tier2 site (KNU) and 2 official Tier3 sites (UOS and KISTI). There can be institutional local resources linked with these tier sites.

KCMS computing meeting is held biweekly (adjustable depending on schedules), chaired by Prof. Intae Yu.
Computing managers are welcomed to present their status and give ideas to improve KCMS computing environment. Users in KCMS are also welcomed to share experiences in the analysis.
Discussion items can be found in KCMS computing Task Force meeting. There is a mailing list in CERN egroup on the computing resources in Korean group cms-kr-tier3@cern.ch. To be included in the mailing list, subscribe yourself or ask Junghwan Goh (jhgoh@cern.ch).

General procedure to use KCMS computing resources

You have to be registered as a KCMS member.
To use CMS grid resources, you must register as a CMS member and create your grid certificate. Full registration procedure and getting grid certificate can be easily done when you visit CERN, but basically you can follow the procedures remotely in Korea. (It is best to visit CERN for your registration. Remote registration is slow and problematic in many cases.)

We recommend you to register to the official tier sites in Korea. There are three official tier sites, you can choose one depending on your location and group policy. Also it is free to register to all sites. Having account in tier site allows you to use local analysis farms, do easy-access of data files, store your large crab output files and share with your collaborators. You can also pull the dataset you are interested in to the site by PhEDEx? request (needs approval by site admin).

Send registration form to site administrators with your information. Some site admins may ask you to be verified by your group leader.
Check the followings for more information.

Name Homepage
Technical info General info
KNU T2 http://t2-cms.knu.ac.kr/
Tier2 @ KNU
D. Han, J. Song
Login : kcms-t2.knu.ac.kr or kcms-t3.knu.ac.kr
Job submission: qsub(torque)
Data access: cluster142.knu.ac.kr
Fill the registration forms(registration form1 registration form2) and send to site administrator. Follow the procedures in the manual page.
UOS T3 Tier3 @ UOS
G. Ryu, K. Choi
Login : gate.sscc.uos.ac.kr (SLC6) or gate2.sscc.uos.ac.kr (SLC5)
Job submission: qsub(torque)
Data access: uosaf0007.sscc.uos.ac.kr
Sent email to admin with general info
KISTI T3 http://linux.kisti.re.kr/cmst3/cmst3.html
Tier3 @ KISTI
S. Roh, G. Kim
Login : ui10.sdfarm.kr:4280
Job submission: condor_submit(condor)
Data access: cms-xrdr.sdfarm.kr
Fill the registration form and sent it to admin. Read the user guide CMS-T3-GUIDE.pdf
KNU ccp analysis farm   Login : ccp.knu.ac.kr
Job submission: qsub (torque)
No PhEDEx?. Copy data from KNU_T2 if needed.
Local analysis farm
SNU Analysis farm     Local analysis farm

User experiences and know-hows are summarised in this page UnofficialGuideKCMSComputing (in Korean).

Using the KCMS computing resources

After registration, you can setup your workarea in your directory. Usually, you are allowed to run test jobs only in the login machine. For jobs with heavy CPU usage, you have to use batch systems. Also user data files must be stored in dedicated storage machine (SE) which are accessable with srm or xrood protocols.

For a standard cmsRun job submission, each sites provide instructions. You can submit your jobs with standard CRAB for grid jobs, local CRAB (if site is configured), create-batch script (ask Junghwan Goh) or submit jobs yourself.

Dataset for each site.

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