1 / 8

SciDAC: Business as Usual?

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).

antionettee
Download Presentation

SciDAC: Business as Usual?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SciDAC: Business as Usual? Perspectives from the TeraScale Supernova Initiative • One Discovery • Three Examples • Multi-Physics • Applied Mathematics • Computer Science • and a little Philosophy Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  2. 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). Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  3. 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. Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  4. 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.) Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  5. 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 Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  6. 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 Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

  7. Addressing TSI’s Bulk Data Transfer Needs: Current Data Generation Rate: 500 Mbps (5 TB/day). • 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. • 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! Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC Atchley, Beck, and Moore (2003)

  8. 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. Anthony Mezzacappa SciDAC PI Meeting, Charleston, SC

More Related