Phase 3 Letter of Intent (1/2)

1
Phase 3 Letter of Intent (1/2)

• Short N Pages
• May Refer to MONARC Internal Notes to Document
  Progress
• Suggested Format Similar to PEP Extension
• Introduction deliverables are realistic
  technical options and the associated resource
  requirements for LHC Computing to be presented
  to the experiments and CERN, in support of
  Computing Model development for the Computing
  TDRs.
• Brief Status Existing Notes
• Motivations for a Common Project --gt
  Justification (1)
• Goals and Scope of the Extension --gt
  Justification (2)
• Schedule Preliminary estimate is 12 Months from
  completion of Phase 2, that will occur with
  the submission of the final Phase 12 Report.
  Final report will contain a proposal for the
  Phase 3 milestones and detailed schedule
• Phase 3A Decision on which prototypes to build
  or exploit
• MONARC/Experiments/Regional Centres Working
  Meeting
• Phase 3B Specification of resources and
  prototype configurations
• Setup of simulation and prototype environment
• Phase 3C Operation of prototypes and of
  simulation analysis of results
• Phase 3D Feedback strategy optimization

2
Phase 3 Letter of Intent (2/2)

• Equipment Needs (Scale specified further in Phase
  3A)
• MONARC Sun E450 server upgrade
• TB RAID Array, GB memory upgrade
• To act as a client to the System in CERN/IT, for
  distributed system studies
• Access to Substantial system in the CERN/IT
  infrastructure consisting of a Linux farm, and
  a Sun-based data server over Gigabit Ethernet
• Access to a Multi-Terabyte robotic tape store
• Non-blocking access to WAN links to some of the
  main potential RC (e.g. 10 Mbps reserved to
  Japan some tens of Mbps to US)
• Temporary use of a large volume of tape media
• Relationship to Other Projects and Groups
• Work in collaboration with CERN/IT groups
  involved databases and large scale data and
  processing services
• Our role is to seek common elements that may be
  used effectively in the experiments Computing
  Models
• Computational Grid Projects in US Cooperate
  in upcoming EU Grid proposals
• US other National Funded efforts with RD
  components
• Submitted to Hans Hoffmann for Information on
  our Intention to Continue
• Copy to Manuel Delfino

3
Phase 3 LoI Status

• Monarc has met its milestones up until now
• Progress Report
• Talks in Marseilles General Simulation
• Testbed Notes 99/4, 99/6, Youheis Note --gt
  MONARC number
• Architecture group notes 99/1-3
• Simulation Appendix of Progress Report
• Short papers (Titles) for CHEP 2000 by January 15

4
MONARC Phase 3 Justification (1)

• General TIMELINESS and USEFUL IMPACT
• Facilitate the efficient planning and design of
  mutually compatible site and network
  architectures, and services
• Among the experiments, the CERN Centre
  and Regional Centres
• Provide modelling consultancy and service to the
  experiments and Centres
• Provide a core of advanced RD activities, aimed
  at LHC computing system optimisation and
  production prototyping
• Take advantage of work on distributed
  data-intensive computingfor HENP this year in
  other next generation projects
• For example in US Particle Physics Data Grid
  (PPDG) of DoE/NGI Joint GriPhyN
  proposal on Computational Data Grids by
  ATLAS/CMS/LIGO/SDSS. Note EU Plans as well.
• See H. Newman, http//www.cern.ch/MONARC/progr
  ess_report/longc7.html

5
MONARC Phase 3 Justification (2A)

• More Realistic Computing Model Development (LHCb
  and Alice Notes)
• Confrontation of Models with Realistic
  Prototypes
• At Every Stage Assess Use Cases Based on Actual
  Simulation, Reconstruction and Physics Analyses
• Participate in the setup of the prototyopes
• We will further validate and develop MONARC
  simulation system using the results of these use
  cases (positive feedback)
• Continue to Review Key Inputs to the Model
• CPU Times at Various Phases
• Data Rate to Storage
• Tape Storage Speed and I/O
• Employ MONARC simulation and testbeds to study CM
  variations, and suggest strategy improvements

6
MONARC Phase 3 Justification (2B)

• Technology Studies
• Data Model
• Data structures
• Reclustering, Restructuring transport operations
• Replication
• Caching, migration (HMSM), etc.
• Network
• QoS Mechanisms Identify Which are important
• Distributed System Resource Management and Query
  Estimators
• (Queue management and Load Balancing)
• Development of MONARC Simulation Visualization
  Toolsfor interactive Computing Model analysis
  (forward reference)

7
MONARC Phase 3 Justification (3)

• Meet Near Term Milestones for LHC Computing
• For example CMS Data Handling Milestones ORCA4
  March 2000 1 Million event fully-simulated data
  sample(s)
• Simulation of data access patterns, and
  mechanisms used to build and/or replicate
  compact object collections
• Integration of database and mass storage
  use (including caching/migration strategy for
  limited disk space)
• Other milestones will be detailed, and/or
  brought forward to meet the actual needs for HLT
  Studies and the TDRs for the Trigger, DAQ,
  Software and Computing and Physics
• ATLAS Geant4 Studies
• Event production and and analysis must be spread
  amongst regional centres, and candidates
• Learn about RC configurations, operations,
  network bandwidth, by modeling real systems, and
  analyses actually with
• Feedback information from real operations into
  simulations
• Use progressively more realistic models to
  develop future strategies

8
MONARC Computing Model Constraints Drive
Strategies

• Latencies and Queuing Delays
• Resource Allocations and/or Advance Reservations
• Time to Swap In/Out Disk Space
• Tape Handling Delays Get a Drive, Find a Volume,
  Mount a Volume, Locate File, Read or Write
• Interaction with local batch and device queues
• Serial operations tape/disk, cross-network,
  disk-diskand/or disk-tape after network transfer
• Networks
• Useable fraction of bandwidth (Congestion,
  Overheads) 30-60 (?)Fraction for event-data
  transfers 15-30 ?
• Nonlinear throughput degradation on loaded or
  poorly configurednetwork paths.
• Inter-Facility Policies
• Resources available to remote users
• Access to some resources in quasi-real time