Summary of Computing Section of Technical Proposal

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1 Summary of Computing Section of Technical Proposal
Data Flow Model Computing Requirements Computing Infrastructure Software Strategy Project Organisation and Management Manpower estimates and costs 9/17/2019 Computing section of LHC-B TP

2 Computing section of LHC-B TP
Status of Documents Draft of Computing Section is available - 5 pages Based on four Computing Notes containing more details LHC-B Computing Tasks Requirements LHC-B Computing Model LHC- B Software Strategy LHC-B Project Plan for Computing Drafts of notes available on Web - still being revised 9/17/2019 Computing section of LHC-B TP

3 Computing section of LHC-B TP
9/17/2019 Computing section of LHC-B TP

4 Computing section of LHC-B TP
Data Flow Model Algorithms used for Level 2/3 triggers similar to those employed in full reconstruction. Issues are : speed, reliability calibration and alignment in real-time output of L2 and L3 used by full reconstruction Size of data store and access speeds 2-3 orders of magnitude higher than current experiments and similar to other LHC experiments Raw data written to storage at 20 MB/s. Similar amount of reconstruction information (14 MB/s) In total capability of storing > 0.4 PB of data/year at 40 MB/s Transparent access to data store by nearly all tasks Alignment of Tracking System is crucial….can be done in real-time because we have so many tracks ~mm with survey many tracks human intervention needed For efficiency don’t redo things if don’t have to e.g. determination of coordinates (since calibration is presumably good) 9/17/2019 Computing section of LHC-B TP

5 Computing Requirements
Estimates of CPU requirements, input/output data volumes based on… simulation - program exists so good estimates Assumptions on evolution of algorithms optimisation (e.g. shower parameterisation) increasing complexity (more detail) new frameworks like GEANT4 (30% improvement) reconstruction - partial information on pattern recognition Extrapolations from existing experiments (need input from HERA-B) analysis algorithms - less well known but needs are smaller Some numbers are ‘targets’ as opposed to ‘benchmarks’ for example, goals for L2/L3 are 10/200 msec (on 1000 Mips CPU) Simulation realistic Reconstruction big unknown because it doesn’t include pattern recognition for tracking assumptions on P.R. Made use truth information For analysis no real input…some input from Guy size of Ntuple catalogue of physics….not crucial as numbers are smaller optimisation - not using shower parameterisation yet complexity - we havent put in all the detail yet Extrapolations from ALEPH but not from HERA-B yet 9/17/2019 Computing section of LHC-B TP

6 Dedicated Installed Processing Power
9/17/2019 Computing section of LHC-B TP

7 Data Storage Requirements
9/17/2019 Computing section of LHC-B TP

8 Computing Infrastructure
Issues are Strategy for evolution of computing model Timescales for investment in computing resources Scalability of cpu farms needed for cpu intensive processing Handling of Petabytes of data stored in a central database Equal access to data for all collaboration institutes We don’t know how to build farms of 1400 cpus Architecture must easily grow and facilitate Not sequential processing but database queries - study access to large data sample 9/17/2019 Computing section of LHC-B TP

9 Evolution of Computing Infrastructure
Steady investment in desktop systems Preparation Phase ( ) need is 1000 Mips and 2 TB of data Use public facilities both inside and outside CERN Increase of 50%/year in requirements for simulation and analysis Impact of test-beam? Implementation Phase ( ) significant increase in our needs (TDRs, full MC, testbeam) invest in private (SHIFT-like) facilities (end 2000/beginning of 2001) Commissioning Phase ( ) assembly of full-scale facilities financing scheme Replace destop every 4 years on average ( 100 SFr/month) increase of 50% /year AT 9/17/2019 Computing section of LHC-B TP

10 Computing section of LHC-B TP
Data Storage Model All event data stored in a single Object Database Storage/retrieval managed by a hierarchical mass storage system Assume 10% of data stored on disk Study options for access of data from any institute CERNtric model - all data stored at and accessed from CERN Regional centres - data distributed between CERN and home labs Cache (part of) data at each institute Depends on technology (network), tariffs, logistics, politics 9/17/2019 Computing section of LHC-B TP

11 Computing section of LHC-B TP
Software Strategy Objectives quality in software ( trigger, prompt reconstruction….) performance - trigger latencies, CPU for bulk processing improve on : knowledge of PEOPLE involved the organisation of the development PROCESS the TECHNOLOGY used Approach use appropriate engineering practices stress importance of architecture - adherence to standards build high quality components (manpower intensive) re-use components wherever possible (manpower efficient) use commercial products when appropriate participate in common (LHC-wide) projects plan well - encourage all members of collaboration to participate 9/17/2019 Computing section of LHC-B TP

12 Software Strategy Technology
Specialised tools that help building software for all life-cycle activities project management (MSProject, communication (web), workflow) verification (inspection, testing) - Purify, Logiscope configuration management (code and documents of all sorts) Technology for life-cycle phases TP states “our intention is to adopt Object Technologies” OOA (analysis), OOD (design), ODBMS (database), C++/Java (language) integration standards (OMG/CORBA, ActiveX/DCOM, RMI/Javabeans) large investment by software industry - commercial tools and products widely available (GUIs, distributed systems) widespread adoption within HEP GEANT4 - new simulation framework re-engineered using OO Event Store/Objectivity Replacement of CERNLIB - OpenGL, IrisExplorer (analysis framework) Adoption by other experiments (BaBar, STAR, ATLAS/CMS,ALICE..) 9/17/2019 Computing section of LHC-B TP

13 Computing section of LHC-B TP
Benefits of OO OO evolved out of addressing issues of “programming-in-the-large” Objects are basis for reusable modules Communication by message passing helps to define interfaces between modules and external systems Design essential features of an object that distinguish it from all other objects - defines crisp boundaries (Abstraction) All internal implementation details are hidden - manage complexity (Encapsulation) Reuse of well designed/tested modules (objects) gives better quality and leads to high productivity Partitioning of work into domains is much easier 9/17/2019 Computing section of LHC-B TP

14 Computing section of LHC-B TP
Drawbacks of OO Field is still developing rapidly and some technologies/products may be superceded Culture change is necessary and , in general, people hate this Significant costs associated with training and re-education OO may not be the last word in software engineering 9/17/2019 Computing section of LHC-B TP

15 Computing section of LHC-B TP
Migration Policy Steps are as follows : Build up a suitable programming environment (e.g. C++, UML, Rose) Develop frameworks for simulation, reconstruction and analysis impetus will come mid ‘98 with release of GEANT4 and LHC++ toolkits Embark on intensive training programme Minimise legacy software - hence set an aggressive schedule Manpower is an important issue consolidation of SICB development need extra (skilled) effort 9/17/2019 Computing section of LHC-B TP

16 Computing section of LHC-B TP
Steering Group Composition - coordinator plus one rep from each project Tasks - Coordination, Planning, Resources Computing Facilities Recon- struction Analysis Simulation DAQ Controls OPS Software Eng.Group Farms Desktop Storage Network Operating System Level 2 FW Level 3 FW Recon FW Calibration Production Framewk Tools GEANT4 Framewk Tools Production Event Builder Readout Network Interfaces Links Crates DAQware DCS LHC Safety Run Control Operations Consoles Shift Crew Enviroment Methods Tools Code Manag. Quality Document. Training Licenses Collab. Re-usable Components Data Management : Event Store, Geometry, Database Utilities, ODBMS Architecture : Frameworks, Component model, Distributed system Toolkits : GUI, Histograms, Communications Utilities : data quality monitoring, event display, bookkeeping 9/17/2019 Computing section of LHC-B TP

17 Links to Sub-detector Groups
Application Project (e.g. Reconstruction) RICH Computing Team Project Leader Vertex RICH Inner Tracker Outer Tracker ECAL HCAL MUON Trigger L0 Trigger L1 Trigger L2/L3 9/17/2019 Computing section of LHC-B TP

18 Computing section of LHC-B TP
Life-Cycle Phases Preparation Phase ( now until end of 2000) Learning collect requirements and develop functional specifications of subsystems evaluate hardware technologies build prototypes Implementation Phase (start ‘01 until end ‘03) Building make technology choices engineer sub-systems Commissioning Phase (start ‘04 until end ‘04) Testing install unit test, integration tests tests under realistic loads (bulk data, realistic real-time tests) Operation Phase (start ‘05 until physics goals archived) Running support adapt and improve 9/17/2019 Computing section of LHC-B TP

19 Computing section of LHC-B TP
Manpower Estimates Group Comments Steering Group DAQ + 1-2/ subdetector Controls Common Project Operations Simulation + 1-2/sub-detector Reconstruction + 1-2/sub-detector Analysis interactive applications Re-usable components Software Engineering Common Project Computing Facilities TOTALS 9/17/2019 Computing section of LHC-B TP

20 Computing section of LHC-B TP
Cost Estimate Initial Investment Cost Item Units Unit Cost 1 Total Cost CPU ( Mips ) 1x10 6 3 SFr 3.0 MSFr Disk 2 (TB) 42 12 kSFr 0.5 MSFr Tape (TB) 420 1 kSFr 0.5 MSFr Total 4.0 MSFr Notes : 1. Taken from industry supplied extrapolations to the year 2005 2. Assume 10% of total data taken will reside on disk Annual Investment Costs Item Units Unit Cost Total Cost Desktop CPU 100 100 SFr/month 100 kSFr Software (LHC++,OS) 100 kSFr CPU 500 kSFR Disk 200 kSFr Tape 500 kSFr Total 1400 kSFr 9/17/2019 Computing section of LHC-B TP

21 Computing section of LHC-B TP
9/17/2019 Computing section of LHC-B TP


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