# Presentation: 154982

## SciDAC: Business as Usual?

- Perspectives from the
- TeraScale Supernova Initiative

**One Discovery**
**Three Examples**
** ****Multi-Physics**
** ****Applied Mathematics**
** ****Computer Science**
**and a little Philosophy**

## Scientific Discovery through Advanced Computing

_**Stationary Accretion Shock Instability (SASI)**_

**Supernova shock wave may become unstable.**
**Instability will **
** ****help drive explosion,**
** ****define explosion’s shape.**
**Operates between the proto-neutron star and the**
**supernova shock wave.**
_**Blondin, Mezzacappa, and DeMarino (2003)**_

**Completely unexpected.**
**Discovered through 2D and 3D (TeraScale) hydrodynamics simulations.**
**1024-cubed problem: **
**~ 1 week on 200 X1 processors.**
**Generating data at the staggering rate of 500 Mbps (5 TB/day).**

## Initial shock location/strength 

**Initial shock location/strength **
**depend on knowledge of nuclear**
**states and their occupation**
**during core collapse.**

**This is a challenge in nuclear computation being addressed by TSI’s nuclear theorists.**

**This challenge is exacerbated by the fact that nuclei increase in size (neutron and proton number)**
**/complexity (population of states, collective excitations) during collapse.**

## Significant change in initial shock location and strength and stellar core profiles when 

**Significant change in initial shock location and strength and stellar core profiles when **
**state of stellar core nuclei computed with more realistic nuclear models and when this **
**new nuclear physics is included in the supernova models. **
**Hix et al. 2003, *****Physical Review Letters*****, 91, 201102.**
**Langanke et al. 2003, *****Physical Review Letters*****, 90, 241102.**

**Merger of two fields at their respective states of the art. (SciDAC enabled.)**

## Combining Scalable Algorithms and Code Performance Analysis

**In conjunction with ****TOPS****, TSI applied mathematicians have developed **
**scalable preconditioners and solvers for the sparse linear systems that **
**arise in our neutrino transport solvers.**
_**2D/3D Multigroup Flux-Limited Diffusion (MGFLD) Transport**_
** ****Sparse Approximate Inverse Preconditioner**
**Saylor, Smolarski, and Swesty (2004)**
** ****Successfully implemented in 2D MGFLD code (V2D).**
_**2D/3D Boltzmann Transport**_
** “****ADI” Preconditioner **
**D’Azevedo et al. (2004)**
** ****Successfully implemented in 1D Boltzmann code (AGILE-BOLTZTRAN).**
** ****Dense LU factorization was used for dense blocks (D’Azevedo).**
** ****Being implemented in 2D/3D Boltzmann code (GenASiS).**
** ****Sparse incomplete LU factorization for dense blocks (D’Azevedo, Eijkhout).**
**Coupled with extensive code performance analysis by ****PERC****, **
***simulations using AGILE-BOLTZTRAN that used to complete ***
***in weeks now complete in days*****.**
** ****Remains our best venue for the exploration of the **
**Nuclear and weak interaction physics **

## As TSI enters “production mode” managing its Workflows has become a paramount issue.

**As TSI enters “production mode” managing its ****Workflows**** has become a paramount issue.**
** ****Ideally, we would like to ****automate**** these workflows.**

**Data Management**
**Networking**
**Visualization**

**These must be viewed together.**

**Collaboration between:**
**SDM**
** ****Arie Shoshani**
** ****Nagiza Samatova**
** ****Guru Kora**
** ****Ian Watkins**
** ****Mladen Vouk**
**Networking**
** ****Beck**
** ****Atchley**
** ****Moore**
** ****Rao**
**Visualization (TSI)**
** ****Blondin**
** ****Toedte**

## Addressing TSI’s Bulk Data Transfer Needs:

- _Addressing TSI’s Bulk Data Transfer Needs:_

***Logistical Networking provided a ***
**Light-Weight**
**Low-Level**
**Deployable         *****... solution.***
**New Paradigm**
**Integrate storage and networking.**
**Multi-source, multi-stream.**
**Easy for TSI members to share data.**

**Atchley, Beck, and Moore (2003)**

***Data transfer rates 200-300 Mbps using TCP/IP!***
**Limit set by ORNL firewall.**
**Greater rates expected**
**outside firewall,**
**other protocols (e.g., Sabul).**
***Direct impact on TSI’s workflow!***

**Current Data Generation Rate:**
**500 Mbps (5 TB/day).**

## Conclusions

**SciDAC has certainly lived up to its name.**
**Enabled scientific discovery through high-performance computing.**
**SciDAC has brought whole communities of researchers together.**
**Has taken science to an entirely new level of realism.**
** ****e.g., state of the art nuclear physics in astrophysics models**
**Has enabled science that otherwise could not have been done.**
** ****e.g., state of the art data management and networking technologies **
**  ****enabling astrophysics simulations**
**Under SciDAC**
**We are growing a new community.**
**We are growing a new culture.**
**What is that feeling?**
**The excitement of meeting new people.**
**The excitement of learning new things.**
**It’s the teamwork, the camaraderie. **
**The excitement of participating in what is a jewel of a program.**
**The excitement of knowing we have a real shot at leaving behind a scientific legacy.**
**The excitement that at the end of the day we can really make a difference.**