NOAO Brown Bag Tucson, AZ March 11, 2008 Jeff Kantor LSST Corporation Requirements Flowdown with LSST SysML and UML Models

NOAO Brown Bag March 11, 2008 Tucson, AZ 2 Presentation Outline LSST Data Management introduction Requirements flow-down Enterprise Architect SysML/UML demonstration

NOAO Brown Bag March 11, 2008 Tucson, AZ 3 Data Management is a distributed system that leverages world-class facilities and cyber-infrastructure Long-Haul Communications Chile - U.S. & w/in U.S. 2.5 Gbps avg, 10 Gbps peak Archive Center NCSA, Champaign, IL 100 to 250 TFLOPS, 75 PB Data Access Centers U.S. (2) and Chile (1) 45 TFLOPS, 87 PB Mountain Summit/Base Facility Cerro Pachon, La Serena, Chile 25 TFLOPS, 150 TB 1 TFLOPS = 10^12 floating point operations/second 1 PB = 2^50 bytes or ~10^15 bytes

NOAO Brown Bag March 11, 2008 Tucson, AZ 4 LSST Data Management provides a unique national resource for research & education Astronomy and astrophysics –Scale and depth of LSST database is unprecedented in astronomy Provides calibrated databases for frontier science Breaks new ground with combination of depth, width, epochs/field Enables science that cannot be anticipated today Cyber-infrastructure and computer science –Requires multi-disciplinary approach to solving challenges Massively parallel image data processing Peta-scale data ingest and data access Efficient scientific and quality analysis of peta-scale data

NOAO Brown Bag March 11, 2008 Tucson, AZ 5 DM system complexity exists but overall is tractable Complexities we have to deal with in DM –Very high data volumes (transfer, ingest, and especially query) –Advances in scale of algorithms for photometry, astrometry, PSF estimation, moving object detection, shape measurement of faint galaxies –Provenance recording and reprocessing –Evolution of algorithms and technology Complexities we DON’T have to deal with in DM –Tens of thousands of simultaneous users (e.g. online stores) –Fusion of remote sensing data from many sources (e.g. earthquake prediction systems) –Millisecond or faster time constraints (e.g. flight control systems) –Very deeply nested multi-level transactions (e.g. banking OLTP systems) –Severe operating environment-driven hardware limitations (e.g. space- borne instruments) –Processing that is highly coupled across entire data set with large amount of inter-process communication (e.g. geophysics 3D Kirchhoff migration)

NOAO Brown Bag March 11, 2008 Tucson, AZ 6 Performance - Nightly processing timeline for a visit meets alert latency requirement Exposure 1 Exposure 2 Shutter close Time (sec) Readout complete Transfer to Base complete Image Processing/ Detection complete Association complete Alert generate complete Shutter close Readout complete Transfer to Base complete Image Processing/ Detection complete 2s6s20s Exposure begins 15s T0 - Start of 60 second latency timer 3s6s20s10s T0 + 51s 2s Exposure begins 15s

NOAO Brown Bag March 11, 2008 Tucson, AZ 7 Archive Center Base Data Access Center Archive Center Trend Line Computing needs show moderate growth

NOAO Brown Bag March 11, 2008 Tucson, AZ 8 Database Volumes Detailed spreadsheet-based analysis done Expecting: –6 petabytes of data, 14 petabytes data+indexes –all tables: ~16 trillion rows (16x10 12 ) –largest table: 3 trillion rows (3x10 12 )

NOAO Brown Bag March 11, 2008 Tucson, AZ 9 Cerro Pachon La Serena Long-haul communications are feasible Over 2 terabytes/second dark fiber capacity available Only new fiber is Cerro Pachon to La Serena (~100 km) 2.4 gigabits/second needed from La Serena to Champaign, IL Quotes from carriers include 10 gigabit/second burst for failure recovery Specified availability is 98% Clear channel, protected circuits

NOAO Brown Bag March 11, 2008 Tucson, AZ 10 Science Requirements Document Telescope, Camera, Survey Reference Designs Data Management Requirements Data Management Design Complete, traceable flow-down from science to system, to data management subsystem Allocation Traceability DMS Sizing Models: Processing, Storage, Communications Allocation Traceability

NOAO Brown Bag March 11, 2008 Tucson, AZ 11 Science Requirements Document System Requirements, Telescope, Camera, Survey Reference Designs Key Specified and Derived Requirements The mission, instrument design, observing cadence and observatory operational requirements drive the DM requirements Data Management Requirements Data Management Design Data Products Images Catalogs Alerts Quality and Performance Statistics Algorithms/Pipelines Astrometric/Photometric Calibration Source Detection Source - Object Association Moving Object Detection/Orbit Matching Alert Processing Deep Detection Calibration Classification Architectural Scalabiity Reliability/Availability Evolution Science and system requirements flow-down using SysML Allocation Traceability System Modeling Language (SysML)

NOAO Brown Bag March 11, 2008 Tucson, AZ 12 DMS Sizing Models Computational Requirements Processing Sustained & peak processing analyzed Tradeoffs considered: Store vs. recompute Types of parallelism Reliability vs cost Storage Sustained & peak I/O rates and storage needs analyzed Tradeoffs considered: Store vs. recompute DBMS vs File System Multi-dimensional access Reliability vs cost Communications Sustained & peak bandwidth analyzed Tradeoffs considered: Transfer and process vs process and transfer Media transfer vs network Reliability vs cost Data Management Requirements Data Management Design Storage and Input/Output Requirements Data Transfer, Replication, And Access Requirements Performance requirements analyzed & feasible

NOAO Brown Bag March 11, 2008 Tucson, AZ 13 Systems Engineering Model for Requirements Flowdown, Traceability & Configuration Control SysML = System Modeling Language SE Model Operational Model Structural/Component Model Requirements Model Other Engineering Analysis Models Performance & Constraints Model FEMAP NX Nastran

NOAO Brown Bag March 11, 2008 Tucson, AZ 14 Requirements Flow SRD Telescope Site Req. Camera Req. Data Management Req. Functional Req. (FPRD) Operational Req. (OCDD) Interface Requirements Outside Constraints System Requirements SysML Model DM Subsystems Req. UML Model T&S Subsystems Req. SysML Model Camera Subsystems Req. LSST Board & Science Council Project Office Change Control Board Project Office Change Control Board Subsystem Group

NOAO Brown Bag March 11, 2008 Tucson, AZ 15 Requirements Hierarchy

NOAO Brown Bag March 11, 2008 Tucson, AZ 16 Rigorous process for software engineering based on wide industry experience (Iconix) Algorithm/Pipeline Data Product Prototypes UML Models Image courtesy of Iconix Software Engineering, Inc. Unauthorized use not permitted. Unified Modeling Language (UML)

NOAO Brown Bag March 11, 2008 Tucson, AZ 17 Demo of Enterprise Architect Tool for SysML and UML System Engineering (SysML model is in “DM SysML.pdf”) Science Requirements DM Functional/Performance Requirements Use Cases Software Engineering (UML model is in “DM UML.pdf”) Use Cases/Robustness Diagrams Class Diagrams/Sequence Diagrams Code