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Jason Leigh spiff@evl.uic

SuperDuperNetworking Transforming Supercomputing … from the point of view of Large Scale Visualization and Collaborative Work. Jason Leigh spiff@evl.uic.edu. A Typical Data Correlation and Visualization Pipeline. Data Source  Correlate/Filter  Render  Display

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Jason Leigh spiff@evl.uic

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  1. SuperDuperNetworking Transforming Supercomputing…from the point of view of Large Scale Visualization andCollaborative Work Jason Leigh spiff@evl.uic.edu

  2. 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. 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. Protocol & data rate independent Calient / Glimmerglass at StarLight & EVL

  4. 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. Photonic Multicast Service Glimmerglass Reflexion Photonic Multicast-capable Switch

  6. 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. 1st Step: Realize Local Area Photonic Multicasting(Visit Booth R2935 to learn how this is done on the OptIPuter)

  8. Quiz: Guess the Mystery Computer with the enormous bandwidth but tiny caches… 2.4GB/s from main memory to graphics (Today’s AGP8X is at 2.1GB/s) 48GB/s! (Today’s Quadro FX3000only has 27GB/s) Tiny caches Memory 32MB Graphics Synthesizer 4MB SIF IPU 128bit bus DMA 16K cache GIF FPU 300MhZMIPS 3 VU0 VU1 Vector processors with several parallel pipelines For distributed, collaborative large scale data visualization, we need a version of this that extends to wide area environments.

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