1. June 29 San FranciscoSciDAC 2005 Terascale Supernova Initiative Discovering New Dynamics of Core-Collapse Supernova Shock Waves John M. Blondin NC State University Scientific Discovery through Advanced Computing

2. June 29 San FranciscoSciDAC 2005

3. June 29 San FranciscoSciDAC 2005 1966 Colgate and White Neutrino-Driven prompt explosion 1985 Bethe and Wilson Shock reheating via neutrino energy deposition 1992 Herant, Benz, and Colgate Convective instability above neutrino-sphere A Long History of Computational Physics…

4. June 29 San FranciscoSciDAC 2005 The Modern Picture…

5. June 29 San FranciscoSciDAC 2005 It all starts with core collapse…

6. June 29 San FranciscoSciDAC 2005 First generation of 2D SN models hinted at a low-order asymmetry in the shock wave at late times (100’s of msec after bounce). Burrows, Hayes & Fryxell 1995

7. June 29 San FranciscoSciDAC 2005 Dynamics of the Supernova Shock Wave When, Where and How is spherical symmetry is broken?

8. June 29 San FranciscoSciDAC 2005 Modeling post-bounce shock

9. June 29 San FranciscoSciDAC 2005 SN Code Verification This post-bounce model provides an opportunity to verify supernova codes against the results of a linear perturbation analysis. Houck and Chevalier 1992 Blondin and Mezzacappa 2005

10. June 29 San FranciscoSciDAC 2005 Spherical Accretion Shock Instability

11. June 29 San FranciscoSciDAC 2005 SASI Standing pressure waves within the cavity of a spherical accretion shock are amplified with each oscillation. The shock becomes significantly distorted after only a few periods. In core-collapse supernovae, SASI will operate in conjunction (competition?) with neutrino-driven convection.

12. June 29 San FranciscoSciDAC 2005

13. June 29 San FranciscoSciDAC 2005 This initial SASI discovery with axisymmetric 2D simulations pointed to the obvious need for models in full 3D. To better understand the challenges of 3D, let us first look at the process of discovery for the initial 2D models. Must move to 3D!

14. June 29 San FranciscoSciDAC 2005 Hurdles for Large-Scale 3D Simulation code Floating points Data output Data transport Visualization and analysis Not a problem Thank you DOE It works Does not work I can’t see!

15. June 29 San FranciscoSciDAC 2005 First Results: SASI Exists in 3D With data stuck on the West Coast, this was science in the dark! 3D Cartesian grid 100 Million zones 100’s of processors 100’s of GB in full run

16. June 29 San FranciscoSciDAC 2005 Science Begins with Data Scientific discovery is done with interactive access to data. Must have interactive access on a large-memory computer for analysis and visualization. Must have high bandwidth in accessing the data. Must have sufficient storage to hold data for weeks/months. Cray X1 Billion-cell simulation in 30 hours generates 4 terabytes Visualization platform Shared file system

17. June 29 San FranciscoSciDAC 2005 Interactive Visualization of TB Datasets A commodity linux cluster provides all the ‘must haves.’ Data is sliced into slabs and stored on local disks on the cluster nodes. EnSight Gold provides an easy visualization solution, including remote client-server operation and collaboration.

18. June 29 San FranciscoSciDAC 2005

19. June 29 San FranciscoSciDAC 2005 We have jumped the hurdle, but there is much more to be gained. Current research in scientific visualization is providing glimpses of very powerful new techniques. The next step is to get these tools into the hands of application scientists so they can explore their data.

20. June 29 San FranciscoSciDAC 2005 LoRS tools / IBP depots

21. June 29 San FranciscoSciDAC 2005 Parallel analysis and vis on distributed data Run Simulation On 100’s to 1000’s of cpus Data Flow Continues to Evolve Supercomputer Analysis Cluster ( flops )( interactive ) Logistical Network

22. June 29 San FranciscoSciDAC 2005

23. June 29 San FranciscoSciDAC 2005

24. June 29 San FranciscoSciDAC 2005

25. June 29 San FranciscoSciDAC 2005

26. June 29 San FranciscoSciDAC 2005

27. June 29 San FranciscoSciDAC 2005 Current ‘full physics’ models in 2 spatial dimensions (256 2 ) produce 70 GB per run. Current ‘limited physics’ models in 3 spatial dimensions (1000 3 ) produce 4 TB per run. We know this problem must be attacked in 3D with accurate nuclear physics and neutrino transport. With advances in code development and computing platforms, we are looking at PB datasets in the near future! Forecast looks challenging