Grids: Why and How (you might use them) J. Templon, NIKHEF VLV T Workshop NIKHEF 06 October 2003.

Slides:



Advertisements
Similar presentations
1 AMY Detector (eighties) A rather compact detector.
Advertisements

31/03/00 CMS(UK)Glenn Patrick What is the CMS(UK) Data Model? Assume that CMS software is available at every UK institute connected by some infrastructure.
High Performance Computing Course Notes Grid Computing.
Highest Energy e + e – Collider LEP at CERN GeV ~4km radius First e + e – Collider ADA in Frascati GeV ~1m radius e + e – Colliders.
T1 at LBL/NERSC/OAK RIDGE General principles. RAW data flow T0 disk buffer DAQ & HLT CERN Tape AliEn FC Raw data Condition & Calibration & data DB disk.
CHEP 2012 – New York City 1.  LHC Delivers bunch crossing at 40MHz  LHCb reduces the rate with a two level trigger system: ◦ First Level (L0) – Hardware.
1 Software & Grid Middleware for Tier 2 Centers Rob Gardner Indiana University DOE/NSF Review of U.S. ATLAS and CMS Computing Projects Brookhaven National.
23/04/2008VLVnT08, Toulon, FR, April 2008, M. Stavrianakou, NESTOR-NOA 1 First thoughts for KM3Net on-shore data storage and distribution Facilities VLV.
1: Operating Systems Overview
POLITEHNICA University of Bucharest California Institute of Technology National Center for Information Technology Ciprian Mihai Dobre Corina Stratan MONARC.
The new The new MONARC Simulation Framework Iosif Legrand  California Institute of Technology.
K.Harrison CERN, 23rd October 2002 HOW TO COMMISSION A NEW CENTRE FOR LHCb PRODUCTION - Overview of LHCb distributed production system - Configuration.
Workload Management Massimo Sgaravatto INFN Padova.
Ian M. Fisk Fermilab February 23, Global Schedule External Items ➨ gLite 3.0 is released for pre-production in mid-April ➨ gLite 3.0 is rolled onto.
CERN/IT/DB Multi-PB Distributed Databases Jamie Shiers IT Division, DB Group, CERN, Geneva, Switzerland February 2001.
Large scale data flow in local and GRID environment V.Kolosov, I.Korolko, S.Makarychev ITEP Moscow.
Hall D Online Data Acquisition CEBAF provides us with a tremendous scientific opportunity for understanding one of the fundamental forces of nature. 75.
L3 Filtering: status and plans D  Computing Review Meeting: 9 th May 2002 Terry Wyatt, on behalf of the L3 Algorithms group. For more details of current.
LOGO OPERATING SYSTEM Dalia AL-Dabbagh
Operating System Review September 10, 2012Introduction to Computer Security ©2004 Matt Bishop Slide #1-1.
Test Of Distributed Data Quality Monitoring Of CMS Tracker Dataset H->ZZ->2e2mu with PileUp - 10,000 events ( ~ 50,000 hits for events) The monitoring.
Workload Management WP Status and next steps Massimo Sgaravatto INFN Padova.
Dynamic Firewalls and Service Deployment Models for Grid Environments Gian Luca Volpato, Christian Grimm RRZN – Leibniz Universität Hannover Cracow Grid.
A Distributed Computing System Based on BOINC September - CHEP 2004 Pedro Andrade António Amorim Jaime Villate.
Alexandre A. P. Suaide VI DOSAR workshop, São Paulo, 2005 STAR grid activities and São Paulo experience.
José M. Hernández CIEMAT Grid Computing in the Experiment at LHC Jornada de usuarios de Infraestructuras Grid January 2012, CIEMAT, Madrid.
ARGONNE  CHICAGO Ian Foster Discussion Points l Maintaining the right balance between research and development l Maintaining focus vs. accepting broader.
Computing and LHCb Raja Nandakumar. The LHCb experiment  Universe is made of matter  Still not clear why  Andrei Sakharov’s theory of cp-violation.
J OINT I NSTITUTE FOR N UCLEAR R ESEARCH OFF-LINE DATA PROCESSING GRID-SYSTEM MODELLING FOR NICA 1 Nechaevskiy A. Dubna, 2012.
Remote Production and Regional Analysis Centers Iain Bertram 24 May 2002 Draft 1 Lancaster University.
BaBar MC production BaBar MC production software VU (Amsterdam University) A lot of computers EDG testbed (NIKHEF) Jobs Results The simple question:
November 7, 2001Dutch Datagrid SARA 1 DØ Monte Carlo Challenge A HEP Application.
Computing Infrastructure Status. LHCb Computing Status LHCb LHCC mini-review, February The LHCb Computing Model: a reminder m Simulation is using.
Grid Workload Management & Condor Massimo Sgaravatto INFN Padova.
Copyright © 2000 OPNET Technologies, Inc. Title – 1 Distributed Trigger System for the LHC experiments Krzysztof Korcyl ATLAS experiment laboratory H.
- Iain Bertram R-GMA and DØ Iain Bertram RAL 13 May 2004 Thanks to Jeff Templon at Nikhef.
Finnish DataGrid meeting, CSC, Otaniemi, V. Karimäki (HIP) DataGrid meeting, CSC V. Karimäki (HIP) V. Karimäki (HIP) Otaniemi, 28 August, 2000.
ALICE Upgrade for Run3: Computing HL-LHC Trigger, Online and Offline Computing Working Group Topical Workshop Sep 5 th 2014.
Grid Lab About the need of 3 Tier storage 5/22/121CHEP 2012, The need of 3 Tier storage Dmitri Ozerov Patrick Fuhrmann CHEP 2012, NYC, May 22, 2012 Grid.
Status of the LHCb MC production system Andrei Tsaregorodtsev, CPPM, Marseille DataGRID France workshop, Marseille, 24 September 2002.
November SC06 Tampa F.Fanzago CRAB a user-friendly tool for CMS distributed analysis Federica Fanzago INFN-PADOVA for CRAB team.
Author - Title- Date - n° 1 Partner Logo EU DataGrid, Work Package 5 The Storage Element.
The ALICE short-term use case DataGrid WP6 Meeting Milano, 11 Dec 2000Piergiorgio Cerello 1 Physics Performance Report (PPR) production starting in Feb2001.
RAL Site Report John Gordon IT Department, CLRC/RAL HEPiX Meeting, JLAB, October 2000.
Large-Scale Computing with Grids Jeff Templon KVI Seminar 17 February 2004.
Common Use Cases for a HEP Common Architecture Layer J. Templon, NIKHEF/WP8.
1 LCG-France sites contribution to the LHC activities in 2007 A.Tsaregorodtsev, CPPM, Marseille 14 January 2008, LCG-France Direction.
Operating Systems David Goldschmidt, Ph.D. Computer Science The College of Saint Rose CIS 432.
EGEE is a project funded by the European Union under contract IST HEP Use Cases for Grid Computing J. A. Templon Undecided (NIKHEF) Grid Tutorial,
V.A. Ilyin,, RIGF, 14 May 2010 Internet and Science: LHC view V.A. Ilyin SINP MSU, e-ARENA.
Data reprocessing for DZero on the SAM-Grid Gabriele Garzoglio for the SAM-Grid Team Fermilab, Computing Division.
Review of Condor,SGE,LSF,PBS
1 Andrea Sciabà CERN Critical Services and Monitoring - CMS Andrea Sciabà WLCG Service Reliability Workshop 26 – 30 November, 2007.
David Adams ATLAS DIAL: Distributed Interactive Analysis of Large datasets David Adams BNL August 5, 2002 BNL OMEGA talk.
Computing for LHC Physics 7th March 2014 International Women's Day - CERN- GOOGLE Networking Event Maria Alandes Pradillo CERN IT Department.
6 march Building the INFN Grid Proposal outline a.ghiselli,l.luminari,m.sgaravatto,c.vistoli INFN Grid meeting, milano.
Bulk Data Transfer Activities We regard data transfers as “first class citizens,” just like computational jobs. We have transferred ~3 TB of DPOSS data.
Computing Issues for the ATLAS SWT2. What is SWT2? SWT2 is the U.S. ATLAS Southwestern Tier 2 Consortium UTA is lead institution, along with University.
1 A Scalable Distributed Data Management System for ATLAS David Cameron CERN CHEP 2006 Mumbai, India.
Distributed Physics Analysis Past, Present, and Future Kaushik De University of Texas at Arlington (ATLAS & D0 Collaborations) ICHEP’06, Moscow July 29,
Markus Frank (CERN) & Albert Puig (UB).  An opportunity (Motivation)  Adopted approach  Implementation specifics  Status  Conclusions 2.
Storage Management on the Grid Alasdair Earl University of Edinburgh.
Meeting with University of Malta| CERN, May 18, 2015 | Predrag Buncic ALICE Computing in Run 2+ P. Buncic 1.
LHCb Computing activities Philippe Charpentier CERN – LHCb On behalf of the LHCb Computing Group.
CrossGrid Workshop, Kraków, 5 – 6 Nov-2001 Distributed Data Analysis in HEP Piotr MALECKI Institute of Nuclear Physics Kawiory 26A, Kraków, Poland.
ATLAS – statements of interest (1) A degree of hierarchy between the different computing facilities, with distinct roles at each level –Event filter Online.
Grid site as a tool for data processing and data analysis
Philippe Charpentier CERN – LHCb On behalf of the LHCb Computing Group
Introduction to Operating Systems
Development of LHCb Computing Model F Harris
Presentation transcript:

Grids: Why and How (you might use them) J. Templon, NIKHEF VLV T Workshop NIKHEF 06 October 2003

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Information I intend to transfer u Why are Grids interesting? Grids are solutions so I will spend some time talking about the problem and show how Grids are relevant. Solutions should solve a problem. u What are Computational Grids? u How are we (high-energy physicists) using Grids? What tools are available? u How might they be of interest to Neutrino Telescopists?

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Our Problem  Place event info on 3D map  Trace trajectories through hits  Assign type to each track  Find particles you want  Needle in a haystack!  This is “relatively easy” case

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, More complex example

interactive physics analysis batch physics analysis batch physics analysis detector event summary data raw data event reprocessing event reprocessing event simulation event simulation analysis objects (extracted by physics topic) Data Handling and Computation for Physics Analysis event filter (selection & reconstruction) event filter (selection & reconstruction) processed data

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Computational Aspects u To reconstruct and analyze 1 event takes about 90 seconds u Most collisions recorded are not what we’re looking for – maybe want as few as one out of a million. But we have to check them all! u Analysis program needs lots of calibration; determined from inspecting results of first pass. u  Each event will be analyzed several times!

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, online system multi-level trigger filter out background reduce data volume level 1 - special hardware 40 MHz (40 TB/sec) level 2 - embedded processors level 3 - PCs 75 KHz (75 GB/sec) 5 KHz (5 GB/sec) 100 Hz (100 MB/sec) data recording & offline analysis One of the four LHC detectors

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Computational Implications (2) u 90 seconds per event to reconstruct and analyze u 100 incoming events per second u To keep up, need either: n A computer that is nine thousand times faster, or n nine thousand computers working together u Moore’s Law: wait 20 years and computers will be 9000 times faster (we need them in 2006!) u Four LHC experiments plus extra work: need >50k computers u Grids: make large numbers of computers work together

So What are Grids Anyway??

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, A bunch of computers is not a Grid u HEP has experience with a couple thousand computers in one place Putting them all in one spot leads to traffic jams CERN can’t pay for it all Someone else controls your resources Can you use them for other (non-CERN) work? BUT

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Distribute computers like users u Most of computer power not at CERN n need to move users’ jobs to available CPU n Better if jobs are sent to CPUs “close” to data they consume u Need computing resource management n How to connect users with available power? u Need data storage management n How to distribute? n What about copies? (Lots of people want access to same data) u Need authorization & authentication for access to resources!

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Grids are Information Information System Information System A-Grid B-Grid

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, What does the Grid do for you? u You submit your work, and the Grid n Finds convenient places for it to be run n Organises efficient access to your data s Caching, migration, replication n Deals with authentication to the different sites that you will be using n Interfaces to local site resource allocation mechanisms, policies n Runs your jobs n Monitors progress and recovers from problems n Tells you when your work is complete u If your task allows, Grid can also decompose your work into convenient execution units based on available resources, data distribution

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, How it works User Interface User submits job description Workload ManagerInformation System Where are resources to do this job? Data Management Service Publish Resource and Service Information Locate Copies of Requested Data

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, What’s There Now? u Job Submission n Marriage of Globus, Condor-G, EDG Workload Manager n Latest version reliable at 99% level u Information System n New System (R-GMA) – very good information model, implementation still evolving n Old System (MDS) – poor information model, poor architecture, but hacks allow 99% “uptime” u Data Management n Replica Location Service – convenient and powerful system for locating and manipulating distributed data; mostly still user-driven (no heuristics) u Data Storage n “Bare gridFTP server” – reliable but mostly suited to disk-only mass store n SRM – no mature implementations

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, VLV T Reconstruction Model Mediterranean 10 Gb/s L1 Trigger Raw Data Cache > 1 TB > 1000 CPUs  Distributed Event Database?  Auto Distributed Files?  Single Mass Store + “Thermal Grid”? StreamService 1 Mb/s This needs work!! 2 Gbit/s is not a problem but you want many x 80 Gbit/s! Dual 1TB Circular Buffers? All connections through single pipe probably bad. Dedicated line to better-connected “redistribution center”? Grid useful here – get a lot but only when you need it! Grid data model applicable, but maybe not computational model …

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Networking Likely OK, Surely Welcome! u History of Internet Land Speed Record n 930 Mbit/sec (NIKHEF/California) 1 year ago n 2.2 Gbit/sec (CERN) six months ago n 5 Gbit/sec today (tests last week from NIKHEF) u This rapid advance results in network people looking for groups who can fill the pipes!!

Jeff Templon – NIKHEF VLV T Workshop, Amsterdam, Conclusions u Grids are working now for workload management in HEP u Data model of VLV T matches Grid data model quite well u Gamma-Ray burst scenario matches Grid computational paradigm well u Network demands appear feasible and will be welcomed u Sounds like a lot of fun!