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M. D.Wolf, K. Schwan, and G. Eisenhauer Georgia Institute of Technology

Remote Visualization Using Low-Level Event Services and Cluster Computing — OR — ECho, cluster computing, and the Access Grid. M. D.Wolf, K. Schwan, and G. Eisenhauer Georgia Institute of Technology. http://www.cc.gatech.edu/projects/ihpcl. Members:. Karsten Schwan, CS Kevin Brennan, ECE

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M. D.Wolf, K. Schwan, and G. Eisenhauer Georgia Institute of Technology

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  1. Remote VisualizationUsing Low-Level Event Servicesand Cluster Computing—OR—ECho, cluster computing, and the Access Grid M. D.Wolf, K. Schwan, and G. Eisenhauer Georgia Institute of Technology

  2. http://www.cc.gatech.edu/projects/ihpcl Members: Karsten Schwan, CS Kevin Brennan, ECE Uzi Landman, PHYS Sudharkar Yalamanchili, ECE Ellis Johnson, ISYE David McDowell, ME Suresh Menon, AE + Research Scientists and Graduate Students

  3. IHPCL Collaborative HPC Applications Spectral2Grid 3d vis & steering transport model Spectral2Grid Access Grid ... Active Filter VisAD 3d Active Interface chemical model information transformation and routing heterogeneous client interfaces or portals historical chemical model results

  4. vs. Undamaged Damaged Undamaged W W L L W / l and L / l l = interatomic spacing Research Application: Molecular Dynamics • Mechanical Engineering • Physics • Chemistry • Aerospace Engineering

  5. Real-Time, “Photographic” Visualization Taken from the same research on the cover of the August 18, 2000 edition of Science.

  6. Media Conversion Raytracing (pvmpov) Molecular Dynamics VRML generation Disk (binary format) every timestep Current Implementation Event Channel Viewer

  7. Raytracing (pvmpov) Molecular Dynamics Disk (binary format) every timestep What We Would Like Event Channel User Portal Event Channel (3D) User Portal AG User Portal

  8. So What’s This Portal? Data Channels Data Channels have Directory Services Data Video • labeling • synchronization • replay • user-defined • transformation • high performance • handle “large” • data feeds High Bandwidth Data Video Video Distributed PowerPoint Video Audio local storage

  9. Event Source Event Sink Event Sink Event Channel Event Sink Event Source Network Delivery

  10. ECho Infrastructure • Event Services for data and control structures • Interoperability • Automatic conversion of data types between platforms • Bindings for C and Java; Fortran almost completed • No centralization, channels are represented by distributed data structures • Local event delivery by subroutine call or queuing • Remote delivery multiplexed over shared communications links (TCP, UDP, Wireless, multicast)

  11. ECho Performance Bandwidth (Mbps) Message size

  12. ECho latency

  13. New Event Channel Source Sink Derived Event Channels Event Channel F( ) Derived Channels extend the ECho Model • F() is a user-specified function, with • on-demand, inline binary code • generation • F() can be dynamically linked into the • source • Next: Third party evaluation of F()

  14. Event Channel Event Channel Event Channel F1() F2() F3() Source Sink Chaining Derivations Event Channel

  15. Sink Sink Chaining Derivations Source Sink F1() F2() F3()

  16. Raytracing (pvmpov) Molecular Dynamics The Next Step... AG Portal AG 3D+AG Portal local Color-coded Data for 2D clients Color-coded Data w/stereo F1() F3() F2()

  17. ECho References • The ECho Event Delivery System, Greg Eisenhauer • A Middleware Toolkit for Client-Initiated Service Specialization, Greg Eisenhauer, Fabian Bustamente and Karsten Schwan, Proceedings of the PODC Middleware Symposium - July 18-20, 2000 • Event Services for High Performance Computing, Greg Eisenhauer, Fabian Bustamente and Karsten Schwan, Proceedings of High Performance Distributed Computing (HPDC-2000) • JECho - Supporting Distributed High Performance Applications with Java Event Channels, Dong Zhou, Karsten Schwan, Greg Eisenhauer and Yuan Chen, To appear at Cluster2000 Downloadable versions available from http://www.cc.gatech.edu/systems/projects/ECho/

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