1. LBNL VACET Activities Hank Childs Computer Systems Engineer - Visualization Group August 24, 2009

2. Director’s Review of CRD | August 24 - 26, 2009 Outline Overview: VACET & VisIt Deployment & Outreach: math infrastructure Research: QDV & parallel streamlines Preparing for the Future: hero runs & VisIt infrastructure

3. Director’s Review of CRD | August 24 - 26, 2009 Outline Overview: VACET & VisIt Deployment & Outreach: math infrastructure Research: QDV & parallel streamlines Preparing for the Future: hero runs & VisIt infrastructure

4. Director’s Review of CRD | August 24 - 26, 2009 VACET Mission and Vision Mission: enable scientific insight for petascale data. Strategy: Leverage sci-vis and analytics software technology as an enabling technology. Vision: adapt, extend, create, and deploy data understanding technologies for science stakeholders Why are we a center? –As a center, well positioned to respond to diverse needs/objectives through coordinated R&D, software engineering, outreach efforts.

5. Director’s Review of CRD | August 24 - 26, 2009 VACET Organization Teams: stakeholder projects, R&D projects, software engineering projects. Executive committee: cross-institutional, cross-team coordination. PIs Bethel/LBNL, Johnson/Utah Executive Committee Bethel/LBNL, Brugger/LLNL, Johnson/Utah, Joy/UCD, Ahern/ORNL + Pascucci/Utah, Childs/LBNL R&D TeamsStakeholder ProjectsSoftware Engineering Teams (per site) Chief Software Engineer, Childs/LBNL

6. Director’s Review of CRD | August 24 - 26, 2009 VisIt is a richly featured, turnkey application for large data. VisIt is an open source, end user visualization and analysis tool for simulated and experimental data –Used by: physicists, engineers, code developers, vis experts –>100K downloads on web R&D 100 award in 2005 Used “heavily to exclusively” on 8 of world’s top 12 supercomputers 27B element Rayleigh-Taylor Instability (MIRANDA, BG/L)

7. Director’s Review of CRD | August 24 - 26, 2009 VisIt has a rich feature set that can impact many science areas. Meshes: rectilinear, curvilinear, unstructured, point, AMR Data: scalar, vector, tensor, material, species Dimension: 1D, 2D, 3D, time varying Rendering (~15): pseudocolor, volume rendering, hedgehogs, glyphs, mesh lines, etc… Data manipulation (~40): slicing, contouring, clipping, thresholding, restrict to box, reflect, project, revolve, … File formats (~85) Derived quantities: >100 interoperable building blocks Many general features: position lights, make movie, etc Queries (~50): ways to pull out quantitative information, debugging, comparative analysis

8. Director’s Review of CRD | August 24 - 26, 2009 VisIt and VACET provide significant mutual leverage. VisIt represented over 50 person-years of effort at the time of VACET being funded –VisIt contains over one million lines of code Eric Brugger, NNSA VisIt lead: “VACET has assumed the lead role in ensuring that VisIt will be able to handle the largest data sets.” 2004-6 User community grows, including AWE & ASC Alliance schools Fall ‘06 VACET is funded Spring ‘08 AWE enters repo 2003 LLNL user community transitioned to VisIt 2005 2005 R&D100 2007 SciDAC Outreach Center enables Public SW repo 2007 Saudi Aramco funds LLNL to support VisIt Spring ‘07 GNEP funds LLNL to support GNEP codes at Argonne Summer‘07 Developers from LLNL, LBL, & ORNL Start dev in repo ‘07-’08 UC Davis & UUtah research done in VisIt repo 2000 Project started ‘07-’08 Partnership with CEA is developed 2008 Institutional support leverages effort from many labs Spring ‘09 More developers Entering repo all the time

9. Director’s Review of CRD | August 24 - 26, 2009 Outline Overview: VACET & VisIt Deployment & Outreach: math infrastructure Research: QDV & parallel streamlines Preparing for the Future: hero runs & VisIt infrastructure

10. Director’s Review of CRD | August 24 - 26, 2009 We have made an impact for APDEC PI: Phil Colella (LBNL), SciDAC Applied Partial Differential Equations Center Accomplishment(s) –Software engineering to “bring product to market”. Performance improvements, interface enhancements, file readers, visual data exploration techniques. Science Impact –Visualization on large AMR data sets, and using parallel platforms. –Trail blazed for future VACET work.

11. Director’s Review of CRD | August 24 - 26, 2009 VACET has improved VisIt’s AMR capabilities significantly. Improvements: –Optimized many, many routines, resulting in end- to-end speedups of >10X –Added critical debugging functionality, such as spreadsheets and the ability to connect with a debugger. –Mapped AMR grids -Macros and python callbacks for customizability. -Responded to over 30 requests for interface changes and bug fixes.

12. Director’s Review of CRD | August 24 - 26, 2009 VACET’s efforts have led to VisIt being adopted by important ASCR stakeholders. + see our review document for 9 more letters of support from SciDAC-funded groups using VisIt

13. Director’s Review of CRD | August 24 - 26, 2009 Outline Overview: VACET & VisIt. Deployment & Outreach: math infrastructure. Research: QDV & parallel streamlines Preparing for the Future: hero runs & VisIt infrastructure

14. Director’s Review of CRD | August 24 - 26, 2009 QDV and Accelerator Modeling Accomplishment: –Algorithms + deployment in VisIt to perform interactive visual data analysis (identify, track, analyze beam particles) in multi-TB simulation data. Science Impact: –Replace serial process that took hours with one that takes seconds. –New capability: rapid data exploration and analysis. SC08 paper Customer: C. Geddes (LBNL)/COMPASS Collaborators: SciDAC SDM Center (FastBit) Tech-X (Accelerator scientists)

15. Director’s Review of CRD | August 24 - 26, 2009 Streamlines represent an activity spanning research to SWE to data insight. Stakeholders: “VisIt is bad at streamlines” Stakeholders: “VisIt is bad at streamlines” “We need parallel streamlines” / “Wow! Parallel streamlines is hard” Deployment effort in VisIt by SEG Research effort: Efficient parallel streamline generation

16. This work has had a broad and varied impact. Used in analysis by SHOCKS center (image courtesy SHOCKS website) Poincare analysis for fusion community Poincare analysis for fusion community Streamlines used in visualization of type II supernova collapse Research vehicle (and delivery vehicle) on streamline generation of AMR data sets. Level 0 only (incorrect) Correctly traversing all AMR levels 217 pin reactor cooling simulation. Run on ¼ of Argonne BG/P.

17. Director’s Review of CRD | August 24 - 26, 2009 This work has had a broad and varied impact. “First light” picture showing mixing of cold and warm air inlets. (Nek5000/Fischer, Argonne, INCITE run)

18. Director’s Review of CRD | August 24 - 26, 2009 Existing parallel integral curve techniques have suffered from load imbalance.  Two extremes: Partition data over processors and pass particles amongst processors −Parallel inefficiency! Partition seed points over processors and process necessary data for advection −Redundant I/O! Notional streamline example Notional streamline example P0 P1 P2 P3 P4 P0 P1 P2 P3 P4

19. Director’s Review of CRD | August 24 - 26, 2009 We have greatly advanced the state of the art for parallel integral curve techniques.  Hybrid solution: Master-slave approach that adapts between parallel inefficiencies and redundant I/O P0 P1 P2 P3 P4 IterationAction 0P0 reads B0, P3 reads B1 1P1 passes points to P0, P4 passes points to P3, P2 reads B0 0: Read Notional streamline example Notional streamline example 1: Pass 1: Read - Decision of when to pass or read is simplified here and based on load of processors owning data. - Heuristic weights against I/O, but allows for redundant I/O - All coordination done by slave masters.

20. Director’s Review of CRD | August 24 - 26, 2009 Outline Overview: VACET & VisIt Deployment & Outreach: math infrastructure Research: QDV & parallel streamlines Preparing for the Future: hero runs & VisIt infrastructure

21. Director’s Review of CRD | August 24 - 26, 2009 Trillion-cell experiment: objectives Research questions: –Is it possible/feasible to run production-quality visual data analysis s/w on large machines and on large data sets? –What obstacles/bottlenecks do we encounter at this level of scale? Why? –VACET’s job: provide production-quality tools for large data. This is demonstrating that these tools are viable.

22. Director’s Review of CRD | August 24 - 26, 2009 Trillion cell experiment methodology: What tools, what machines, what data? Application: VisIt 1.11.1 –VisIt is the first and only visualization application that is part of the “Joule” metric Machines: Cray (franklin/LBL, jaguar/ORNL), BG/P (dawn/LLNL), AIX (purple/LLNL), Linux (Juno/LLNL), Sun Linux (ranger/UTexas) Data: –512 3 sample data, astrophysics simulation (courtesy T. Mezzacappa, B. Messer, S. Bruenn, R. Budjiara) –Upsampled to target problem size –Data sizes ranged to 1T (for 16K cores) to 4T (for 64K cores), with 0.5T/8K for AIX/Purple

23. Director’s Review of CRD | August 24 - 26, 2009 Trillion cell experiment methodology: What techniques? Two common visualization techniques: –Isocontouring, volume rendering 2T zones, 32K procs on Jaguar 2T zones, 32K procs on Franklin

24. Director’s Review of CRD | August 24 - 26, 2009 Trillion cell experiment “speed bumps” Application bottleneck: many-to-one status update –Workaround for study, fix to appear in future release of VisIt Application optimization: an NxN buffer for communication, which works well at small scale, proved problematic at large scale. –Workaround: remove optimization, evaluate best course of action for future VisIt release. System issues –Loading shared libraries takes a long time, as much as 5 minutes. Potential fix: implement VisIt plugins as static libraries.

25. Director’s Review of CRD | August 24 - 26, 2009 Trillion cell experiment: Significance of Results Production tool (VisIt) runs effectively at high concurrency, on large problem sizes, and on diverse platforms. –Test of visual data analysis infrastructure –Infrastructure is the underpinning of many different algorithms, not just isocontouring or volume rendering. Minor fixes to become part of production VisIt release (later this year). Successfully processed “tomorrow’s data today.” ~1980~2000~2020 1M 1B1T We are here

26. Director’s Review of CRD | August 24 - 26, 2009 VACET has contributed more than just algorithms and research to VisIt. Production software: bug tracking, regression testing, regular releases Through our efforts, VisIt now feels much more like an open source project: –Transitioned software repository to NERSC; now accessible to a large community. ~30 developers with write access from 10 institutions –Public mailing lists, archived and searchable. ~300 subscribers, get ~300 posts per month –Wiki pages on usage and development.

27. Director’s Review of CRD | August 24 - 26, 2009 Summary The LBNL portion of VACET has made a huge impact in the ASCR community –In deployment, in research, and in paving the way for the future VACET is partnering with many researchers in the ASCR community. VisIt, the production visualization tool for VACET, is being developed by a vibrant community and has demonstrated applicability at the petascale. LBNL is a major center of gravity for the VisIt project.