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Requirements Flowdown with LSST SysML and UML Models. NOAO Brown Bag Tucson, AZ March 11, 2008 Jeff Kantor LSST Corporation. Presentation Outline. LSST Data Management introduction Requirements flow-down Enterprise Architect SysML/UML demonstration.
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Requirements Flowdown with LSST SysML and UML Models NOAO Brown Bag Tucson, AZ March 11, 2008 Jeff Kantor LSST Corporation
Presentation Outline • LSST Data Management introduction • Requirements flow-down • Enterprise Architect SysML/UML demonstration NOAO Brown Bag March 11, 2008 Tucson, AZ
Data Management is a distributed system that leverages world-class facilities and cyber-infrastructure Archive Center NCSA, Champaign, IL 100 to 250 TFLOPS, 75 PB Data Access Centers U.S. (2) and Chile (1) 45 TFLOPS, 87 PB Long-Haul Communications Chile - U.S. & w/in U.S. 2.5 Gbps avg, 10 Gbps peak 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
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
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
Performance - Nightly processing timeline for a visit meets alert latency requirement Exposure 1 Image Processing/ Detection complete Shutter close Readout complete Transfer to Base complete Exposure begins 15s 2s 6s 20s T0 - Start of 60 second latency timer T0 + 51s Time (sec) Exposure 2 15s 2s 6s 3s 20s 10s 10s Image Processing/ Detection complete Exposure begins Shutter close Readout complete Transfer to Base complete Association complete Alert generate complete NOAO Brown Bag March 11, 2008 Tucson, AZ
Computing needs show moderate growth Archive Center Base Data Access Center Archive Center Trend Line NOAO Brown Bag March 11, 2008 Tucson, AZ
Database Volumes • Detailed spreadsheet-based analysis done • Expecting: • 6 petabytes of data, 14 petabytes data+indexes • all tables: ~16 trillion rows (16x1012) • largest table: 3 trillion rows (3x1012) NOAO Brown Bag March 11, 2008 Tucson, AZ
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
Complete, traceable flow-down from scienceto system, to data management subsystem DMS Sizing Models: Processing, Storage, Communications Science Requirements Document Telescope, Camera, Survey Reference Designs Data Management Requirements Data Management Design Allocation Allocation Traceability Traceability NOAO Brown Bag March 11, 2008 Tucson, AZ
Science and system requirements flow-down using SysML • 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 Requirements Document System Requirements, Telescope, Camera, Survey Reference Designs Allocation Traceability System Modeling Language (SysML) NOAO Brown Bag March 11, 2008 Tucson, AZ
Performance requirements analyzed & feasible DMS Sizing Models Data Management Requirements Data Management Design 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 Storage and Input/Output Requirements Data Transfer, Replication, And Access Requirements NOAO Brown Bag March 11, 2008 Tucson, AZ
Requirements Model Operational Model Performance & Constraints Model SE Model Systems Engineering Model for Requirements Flowdown, Traceability & Configuration Control Structural/Component Model Other Engineering Analysis Models FEMAP NX Nastran SysML = System Modeling Language NOAO Brown Bag March 11, 2008 Tucson, AZ
Requirements Flow LSST Board & Science Council SRD System Requirements Project Office Change Control Board Outside Constraints Functional Req. (FPRD) Operational Req. (OCDD) Interface Requirements Project Office Change Control Board Telescope Site Req. Camera Req. Data Management Req. SysML Model T&S Subsystems Req. Camera Subsystems Req. DM Subsystems Req. Subsystem Group SysML Model UML Model NOAO Brown Bag March 11, 2008 Tucson, AZ
Requirements Hierarchy NOAO Brown Bag March 11, 2008 Tucson, AZ
Rigorous process for software engineeringbased on wide industry experience (Iconix) Unified Modeling Language (UML) UML Models Algorithm/Pipeline Data Product Prototypes Image courtesy of Iconix Software Engineering, Inc. Unauthorized use not permitted. NOAO Brown Bag March 11, 2008 Tucson, AZ
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 NOAO Brown Bag March 11, 2008 Tucson, AZ