1. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) SuperDuperNetworking Transforming Supercomputing …from the point of view of Large Scale Visualization and Collaborative Work Jason Leigh spiff@evl.uic.edu

2. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) A Typical Data Correlation and Visualization Pipeline Data Source  Correlate/Filter  Render  Display Data Source  Render  Display Data Source  Render + Display Data Source  Correlate  Render + Display Data Source + Correlate  Render + Display Data Source + Correlate  Render  Display Things to notice: -Pipelines are static for long periods of time- NOT like web surfing- so…. -Routing is not crucial. -Program code is tiny compared to volume of data processed. Caching won’t help much- so…. -Need to stream lots of data through fast concurrent pipelines! -Need pipelines to be optimized from end to end.

3. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) Experiment to Use Inexpensive Photonic Switches as an alternative to traditional million $ routers to provide application-controlled deterministic network paths/pipelines. Long haul link The cross connections are application- programmable. Calient / Glimmerglass at StarLight & EVL Protocol & data rate independent

4. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) In Collaborative Work, Data or Visualization needs to be Distributed to Collaborating Sites Data Source  Correlate  Render  Display Data Source  Render + Display Data Source  Render  Display Data Source  Correlate  Render + Display Data Source + Correlate  Render + Display Data Source + Correlate  Render  Display

5. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) Photonic Multicast Service Glimmerglass Reflexion Photonic Multicast-capable Switch

6. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) Photonically Multicasting a Visualization Challenges: Need to augment traditional Routing and Wavelength Assignment algorithms to consider photonic multicast constraints. Need extreme speed reliable multicast protocol

7. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) 1 st Step: Realize Local Area Photonic Multicasting (Visit Booth R2935 to learn how this is done on the OptIPuter)

8. University of Illinois at Chicago Electronic Visualization Laboratory (EVL) Quiz: Guess the Mystery Computer with the enormous bandwidth but tiny caches… Memory 32MB VU0 300MhZ MIPS 3 IPU DMA VU1 SIF 128bit bus Graphics Synthesizer 4MB GIF 16K cache FPU 2.4GB/s from main memory to graphics (Today’s AGP8X is at 2.1GB/s) 48GB/s! (Today’s Quadro FX3000 only has 27GB/s) Vector processors with several parallel pipelines Tiny caches For distributed, collaborative large scale data visualization, we need a version of this that extends to wide area environments.