1. Dave Morrison, CHEP, February 7, 2000 What we’re doing Why we’re doing it What we’ve learned by doing it PHENIX Offline Computing David Morrison Brookhaven National Laboratory

2. Dave Morrison, CHEP, February 7, 2000 a word from our sponsors... large collaboration (>400 physicists) large, complex detector –~300,000 channels –11 different detector subsystems large volume of data, large number of events –20 MB/sec for 9 months each year –10 9 Au+Au events each year broad physics program –partly because RHIC itself is very flexible –Au+Au at 100+100 GeV/A, spin polarized p+p, and everything in-between –muons, electrons, hadrons, photons

3. Dave Morrison, CHEP, February 7, 2000 from the PHENIX photo album DPM, in hardhat

4. Dave Morrison, CHEP, February 7, 2000 the eightfold way of PHENIX offline computing know your physics program –for PHENIX, event processing rather than event selection know your constraints –money, manpower... and tape mounts avoid “not invented here” syndrome: beg, borrow, collaborate –doesn’t automatically imply use of commercial products focus on modularity, interfaces, abstract base classes viciously curtail variety of architecture/OS –Linux, Solaris data management and data access are really hard problems –don’t rely on fine-grained random access to 100’s of TB of data everyone has their favorite reference works... –Design Patterns (Gamma et al) run-time aggregation, shallow inheritance trees –The Mythical Man-Month (Brooks) avoid implementation by committee

5. Dave Morrison, CHEP, February 7, 2000 building blocks small group of “core” offline developers –M. Messer, K. Pope, M. Velkovsky, M. Purschke, D. Morrison, (M. Pollack) large number of computer-savvy subsystem physicists –recruitment via “help wanted” list of projects that need people PHENIX object-orented library, PHOOL (see talk by M. Messer) –object-oriented analysis framework analysis modules all share common interface –type-safe, flexible data manager extensive use of RTTI, avoids (void *) casts by users ROOT I/O used for persistency –“STL” operations on collection of modules or data nodes varied OO views on analysis framework design –ranging from passive data to “event, reconstruct thyself” –PHOOL follows a hybrid approach migrated to PHOOL from STAF in early 1999 –no user code modified (~120,000 LOC)

6. Dave Morrison, CHEP, February 7, 2000 more blocks lots of physics-oriented objects in PHENIX code –geometry, address/index objects, track models, reconstruction file catalog –metadata management, tracks related files, tied in with run info DB “data carousel” for retrieving files from HPSS –retrieval seen as group-level activity (subsystems, physics working groups) –carousel optimizes file retrieval, mediates resource usage between groups –scripts on top of IBM-written batch system event display(s) –very much subsystem-centered efforts; all are ROOT-based –clearly valuable for algorithm development and debugging –value for PHENIX physics analysis much less clear GNU build system, Mozilla-derived recompilation (poster M. Velkovsky) –autoconf, automake, libtool, Bonsai, Tinderbox, etc. –capable, robust, widely used by large audience on variety of platforms –feedback loop for code development

7. Dave Morrison, CHEP, February 7, 2000 databases in PHENIX Objectivity used for “archival” database needs –Objy used in fairly “mainstream” manner all Objy DBs are resident online (not storing event data) –autonomous partitions, data replicated between counting house, RCF –RCF (D. Stampf) ported Objy to Linux PdbCal class library aimed at calibration DB application –insulates typical user from Objectivity –objects stored with validity period, versioning –usable interactively from within ROOT mySQL used for other database applications –Bonsai, Tinderbox system uses mySQL –heavily used in “data carousel”

8. Dave Morrison, CHEP, February 7, 2000 simplified data flow Objectivity federated DB calibrations & conditions counting house disk NFS disk analysis farm HPSS

9. Dave Morrison, CHEP, February 7, 2000 subclasses of abstract “Eventiterator” class used to read raw data –from online pool, file, or fake test events - user code unchanged online control architecture based on CORBA “publish-subscribe” Java used in counting house for GUIs, CORBA subsystem reconstruction code uses STL, design patterns –not unusual to hear “singleton”, “iterator” at computing meetings OO emerging out of subsystems faster than from core offline crew OO ubiquitous, mainstream in PHENIX

10. Dave Morrison, CHEP, February 7, 2000 OO experiences no Fortran in new post-simulation code –sidestepped many awkward F77/C++ issues, allowed OO to permeate loosely coupled, short hierarchy design working well –information localization on top of information encapsulation –allows decoupled, independent development no formal design tools, but lots of cloudy chalkboard diagrams –usually just a few interacting classes social engineering as important as software engineering –OO not science-fiction, not difficult... and it’s here to stay –lots of hands-on examples, people are usually pleasantly surprised

11. Dave Morrison, CHEP, February 7, 2000 more OO experiences OO was oversold (not by us!) as a computing panacea –does make big computing problem tractable, not trivial –occasional need for internal “public-relations” cognizance of “distance” between concepts advocated by developers and those held by users –e.g., CORBA IDL a great thing; tough to sell to collaboration at-large takes time and effort to “get it”, to move beyond “F77++” –general audience OO and C++ tutorials have helped –also work closely with someone from each subsystem - helps the OO “meme” take hold

12. Dave Morrison, CHEP, February 7, 2000 summary PHENIX computing is essentially ready for physics data –use of PHOOL proven very successful during “mock data challenge” ObjectivityDB is primary database technology used throughout PHENIX reasonably conventional file-oriented data processing model loosely coupled, shallow hierarchy OO design –common approach across online and offline computing several approaches to recruiting, stretching scarce manpower –deliberate, explicit choice by collaboration to move to OO –recruit manpower from detector subsystems –loosely coupled OO design aids loosely coupled development OO has slowed implementation, but has been indispensable for design PHENIX will analyze physics data because of OO, not in spite of it