1 / 26

The OptIPuter Project – Removing Bandwidth as an Obstacle In Data Intensive Sciences

The OptIPuter Project – Removing Bandwidth as an Obstacle In Data Intensive Sciences. Opening Remarks OptIPuter Team Meeting University of California, San Diego February 6, 2003. Dr. Larry Smarr Director, California Institute for Telecommunications and Information Technologies

banyan
Download Presentation

The OptIPuter Project – Removing Bandwidth as an Obstacle In Data Intensive Sciences

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. The OptIPuter Project – Removing Bandwidth as an Obstacle In Data Intensive Sciences Opening Remarks OptIPuter Team Meeting University of California, San Diego February 6, 2003 Dr. Larry Smarr Director, California Institute for Telecommunications and Information Technologies Harry E. Gruber Professor, Dept. of Computer Science and Engineering Jacobs School of Engineering, UCSD

  2. The Move to Data-Intensive Science & Engineering-e-Science Community Resources Sloan Digital Sky Survey ALMA LHC ATLAS

  3. Why Optical Networks Are Emerging as the 21st Century Driver for the Grid Scientific American, January 2001 Parallel Lambdas Will Drive This Decade The Way Parallel Processors Drove the 1990s

  4. A LambdaGrid Will Be the Backbone for an e-Science Network Apps Middleware Clusters C O N T R O L P L A N E Dynamically Allocated Lightpaths Switch Fabrics Physical Monitoring Source: Joe Mambretti, NU

  5. The Biomedical Informatics Research Network a Multi-Scale Brain Imaging Federated Repository BIRN Test-beds: Multiscale Mouse Models of Disease, Human Brain Morphometrics, and FIRST BIRN (10 site project for fMRI’s of Schizophrenics) NIH Plans to Expand to Other Organs and Many Laboratories

  6. GEON’s Data Grid Team Has Strong Overlap with BIRN and OptIPuter • Learning From The BIRN Project • The GEON Grid: • Heterogeneous Networks, Compute Nodes, Storage • Deploy Grid And Cluster Software Across GEON • Peer-to-Peer Information Fabric for Sharing: • Data, Tools, And Compute Resources NSF ITR Grant $11.25M 2002-2007 Two Science “Testbeds” Broad Range Of Geoscience Data Sets Source: Chaitan Baru, SDSC, Cal-(IT)2

  7. NSF’s EarthScope Rollout Over 14 Years Starting With Existing Broadband Stations

  8. Data Intensive Scientific Applications Require Experimental Optical Networks • Large Data Challenges in Neuro and Earth Sciences • Each Data Object is 3D and Gigabytes • Data are Generated and Stored in Distributed Archives • Research is Carried Out on Federated Repository • Requirements • Computing Requirements  PC Clusters • Communications  Dedicated Lambdas Over Fiber • Data  Large Peer-to-Peer Lambda Attached Storage • Visualization  Collaborative Volume Algorithms • Response • OptIPuter Research Project

  9. OptIPuter Inspiration--Node of a 2009 PetaFLOPS Supercomputer 24 Bytes wide 240 GB/s DRAM – 16 GB 64/256 MB - HIGHLY INTERLEAVED 5 Terabits/s DRAM - 4 GB - HIGHLY INTERLEAVED MULTI-LAMBDA Optical Network CROSS BAR Coherence • GB/s 2nd LEVEL CACHE 2nd LEVEL CACHE 8 MB 8 MB 24 Bytes wide 240 GB/s VLIW/RISC CORE 40 GFLOPS 10 GHz VLIW/RISC CORE 40 GFLOPS 10 GHz ... Updated From Steve Wallach, Supercomputing 2000 Keynote

  10. Global Architecture of a 2009 COTS PetaFLOPS System 128 Die/Box 4 CPU/Die • meters= • 50 nanosec Delay 3 4 ... 5 2 16 1 17 64 ALL-OPTICAL SWITCH 18 63 ... ... 32 49 48 Multi-Die Multi-Processor ... 33 47 46 I/O Systems Become GRID Enabled LAN/WAN Source: Steve Wallach, Supercomputing 2000 Keynote

  11. From SuperComputers to SuperNetworks--Changing the Grid Design Point • The TeraGrid is Optimized for Computing • 1024 IA-64 Nodes Linux Cluster • Assume 1 GigE per Node = 1 Terabit/s I/O • Grid Optical Connection 4x10Gig Lambdas = 40 Gigabit/s • Optical Connections are Only 4% Bisection Bandwidth • The OptIPuter is Optimized for Bandwidth • 32 IA-64 Node Linux Cluster • Assume 1 GigE per Processor = 32 gigabit/s I/O • Grid Optical Connection 4x10GigE = 40 Gigabit/s • Optical Connections are Over 100% Bisection Bandwidth

  12. Convergence of Networking Fabrics • Today's Computer Room • Router For External Communications (WAN) • Ethernet Switch For Internal Networking (LAN) • Fibre Channel For Internal Networked Storage (SAN) • Tomorrow's Grid Room • A Unified Architecture Of LAN/WAN/SAN Switching • More Cost Effective • One Network Element vs. Many • One Sphere of Scalability • ALL Resources are GRID Enabled • Layer 3 Switching and Addressing Throughout Source: Steve Wallach, Chiaro Networks

  13. The UCSD OptIPuter Deployment The OptIPuter Experimental UCSD Campus Optical Network ½ Mile To CENIC Phase I, Fall 02 Phase I, Fall 02 Phase II, 2003 Phase II, 2003 Collocation point Collocation point Production Router SDSC SDSC SDSCAnnex SDSCAnnex Preuss High School JSOE Engineering CRCA Arts Medicine SOM UndergradCollege 6thCollege Chemistry Phys. Sci -Keck Node M Collocation Chiaro Router SIO Earth Sciences Source: Phil Papadopoulos, SDSC; Greg Hidley, Cal-(IT)2

  14. Metro Optically Linked Visualization Wallswith Industrial Partners Set Stage for Federal Grant • Driven by SensorNets Data • Real Time Seismic • Environmental Monitoring • Distributed Collaboration • Emergency Response • Linked UCSD and SDSU • Dedication March 4, 2002 Linking Control Rooms UCSD SDSU Cox, Panoram, SAIC, SGI, IBM, TeraBurst Networks SD Telecom Council 44 Miles of Cox Fiber

  15. National Light Rail- Serving Very High-End Experimental and Research Applications • Extension of CalREN-XD Dark Fiber Network • Serves Network Researchers in California Research Institutions • Four UC Institutes, USC/ISI, Stanford and CalTech • 10Gb Wavelengths (OC-192c or 10G LANPHY) • Dark Fiber • Point-Point, Point-MultiPoint 1G Ethernet Possible • NLR is a Dark Fiber National Footprint • 4 - 10GB Wavelengths Initially • Capable of 40 10Gb Wavelengths at Build-Out • Partnership model John Silvester, Dave Reese, Tom West-CENIC

  16. National Light Rail Footprint Layer 1 Topology SEA POR SAC BOS NYC CHI OGD DEN SVL CLE WDC PIT FRE KAN RAL NAS STR LAX PHO WAL ATL SDG STH DAL JAC 15808 Terminal, Regen or OADM site (OpAmp sites not shown) Fiber route John Silvester, Dave Reese, Tom West-CENIC

  17. Calient Lambda Switches Now Installed at StarLight and NetherLight Source: Maxine Brown

  18. Amplified Collaboration Environments CollaborativePassive Stereo Display Collaborative Tiled Display Accessgrid MultisiteVideo Conferencing Collaborative Touch ScreenWhiteboard Wireless Laptops & Tablet PCs To Steer The Displays Source: Jason Leigh

  19. The OptIPuter 2003 Experimental Network Wide Array of Vendors

  20. OptIPuter Software Research • Near-term Goals: • Build Software To Support Applications With Traditional Models • High Speed IP Protocol Variations (RBUDP, SABUL, …) • Switch Control Software For DWDM Management And Dynamic Setup • Distributed Configuration Management For OptIPuter Systems • Long-Term Goals: • System Model Which Supports: • Grid • Single System • Multi-System Views • Architectures Which Can: • Harness High Speed DWDM • Exploit Flexible Dispersion Of Data And Computation • New Communication Abstractions & Data Services • Make Lambda-Based Communication Easily Usable • Use DWDM to Enable Uniform Performance View Of Storage Source: Andrew Chien, UCSD

  21. Photonic Data Services & OptIPuter 6. Data Intensive Applications (UCI) 5a. Storage (UCSD) 5b. Data Services – SOAP, DWTP, (UIC/LAC) 4. Transport – TCP, UDP, SABUL,… (USC,UIC) 3. IP 2. Photonic Path Serv. – ODIN, THOR,... (NW) 1. Physical Source: Robert Grossman, UIC/LAC

  22. OptIPuter is Exploring Quanta as a High Performance Middleware • Quanta Is A High Performance Networking Toolkit / API • Quanta Uses Reliable Blast UDP: • Assumes An Over-Provisioned Or Dedicated Network • Excellent For Photonic Networks • Don’t Try This On Commodity Internet! • It Is Fast! • It Is Very Predictable • We Give You A Prediction Equation To Predict Performance • It Is Most Suited For Transferring Very Large Payloads • RBUDP, SABUL, and Tsunami Are All Similar Protocols That Use UDP For Bulk Data Transfer Source: Jason Leigh, UIC

  23. XCP Is A New Congestion Control SchemeWhich is Good for Gigabit Flows Better Than TCP Almost Never Drops Packets Converges To Available Bandwidth Very Quickly, ~1Round Trip Time Fair Over Large Variations In Flow Bandwidth and RTT Supports existing TCP semantics Replaces Only Congestion Control, Reliability Unchanged No Change To Application/Network API Status To Date: Simulations and SIGCOMM Paper (MIT). See Dina Katabi, Mark Handley, and Charles Rohrs, "Internet Congestion Control for Future High Bandwidth-Delay Product Environments." ACM SIGCOMM 2002, August 2002. http://ana.lcs.mit.edu/dina/XCP/ Current: Developing Protocol, Implementation Extending Simulations (ISI) Source: Aaron Falk, Joe Bannister, ISI USC

  24. Multi-Lambda Security Research • Security Frequently Defined Through Three Measures: • Integrity, Confidentiality, And Reliability (”Uptime”) • Can These Measures Can Be Enhanced By Routing Transmissions Over Multiple Lambdas Of Light? • Can Confidentiality Be Improved By Dividing The Transmission Over Multiple Lambdas And Using “Cheap” Encryption? • Can Integrity Be Ensured Or Reliability Be Improved Through Sending Redundant Transmissions And Comparing? Source: Goodrich, Karin

  25. Research on Developing an Integrated Control Plane Gigabit Stream Bursty Traffic Tera/Peta Stream Megabit Stream Multiple User Data Planes Optical Burst Switching Lambda Inverse Multiplexing Logical Label Switching Optical Lambda Switching Integrated Control Plane Source: Oliver Yu, UIC

  26. OptIPuter Transforms Individual Laboratory Visualization, Computation, & Analysis Facilities Anatomy Neuroscience Visible Human ProjectNLM, Brooks AFB, SDSC Volume Explorer Dave Nadeau, SDSC, BIRNSDSC Volume Explorer Fast polygon and volume rendering with stereographics + GeoWall = 3D APPLICATIONS: Underground Earth Science Earth Science GeoFusion GeoMatrix Toolkit Rob Mellors and Eric Frost, SDSUSDSC Volume Explorer The Preuss School UCSD OptIPuter Facility

More Related