TITAN: A Next-Generation Infrastructure for Integrating and Communication

1. TITAN: A Next-Generation Infrastructure for Integrating and Communication David E. Culler Computer Science Division U.C. Berkeley NSF Research Infrastructure Meeting Aug 7, 1999

2. Project Goal: • “Develop a new type of system which harnesses breakthrough communications technology to integrate a large collection of commodity computers into a powerful resource pool that can be accessed directly through its constituent nodes or through inexpensive media stations.” • SW architecture for global operating system • programming language support • advanced applications • multimedia application development NSF RI 99

3. Computational and Storage Core • architecture • operating systems • compiler, language, and library • High Speed Networking • Multimedia Shell • Driving Applications Project Components The Building is the Computer NSF RI 99

4. Use what you build, learn from use,... Develop Enabling Systems Technology Develop Driving Applications NSF RI 99

5. Highly Leveraged Project • Large industrial contribution • HP media stations • Sun compute stations • Sun SMPs • Intel media stations • Bay networks ATM, ethernet • Enabled several federal grants • NOW • Titanium, Castle • Daedalus, Mash • DLIB • Berkeley Multimedia Research Center NSF RI 99

6. Landmarks • Top 500 Linpack Performance List • MPI, NPB performance on par with MPPs • RSA 40-bit Key challenge • World Leading External Sort • Inktomi search engine • NPACI resource site Sustains 500 MB/s disk bandwidth and1,000 MB/s network bandwidth NSF RI 99

7. Sample of 98 Degrees from Titan • Amin Vahdat: WebOS • Steven Lumetta: Multiprotocol Communication • Wendy Heffner: Multicast Communication Protocols • Doug Ghormley: Global OS • Andrea Dusseau: Implicit Co-scheduling • Armando Fox: TACC Proxy Architecture • John Byers: Fast, Reliable Bulk Communication • Elan Amir: Media Gateway • David Bacon: Compiler Optimization • Kristen Wright: Scalable web cast • Jeanna Neefe: xFS • Steven Gribble: Web caching • Ian Goldberg: Wingman • Eshwar Balani: WebOS security • Paul Gautier: Scalable Search Engines NSF RI 99

8. Results • Constructed three prototypes, culminating in 100 processor UltraSparc NOW + three extensions • GLUnix global operating system layer • Active Messages providing fast, general purpose user-level communication • xFS cluster file system • Fast sockets, MPI, and SVM • Titanium and Split-C parallel languages • ScaLapack libraries • Heavily used in dept. and external research => instrumental in establishing clusters as a viable approach to large scale computing => transitioned to an NPACI experimental resource • The Killer App: Scalable Internet Services NSF RI 99

9. First HP/fddi Prototype • FDDI on the HP/735 graphics bus. • First fast msg layer on non-reliable network NSF RI 99

10. SparcStation ATM NOW • ATM was going to take over the world. • Myrinet SAN emerged The original INKTOMI NSF RI 99

11. Technological Revolution • The “Killer Switch” • single chip building block for scalable networks • high bandwidth • low latency • very reliable • if it’s not unplugged => System Area Networks • 8 bidirectional ports of 160 MB/s each way • < 500 ns routing delay • Simple - just moves the bits • Detects connectivity and deadlock NSF RI 99

12. 100 node Ultra/Myrinet NOW NSF RI 99

13. NOW System Architecture Parallel Apps Large Seq. Apps Sockets, Split-C, MPI, HPF, vSM Global Layer UNIX Process Migration Distributed Files Network RAM Resource Management UNIX Workstation UNIX Workstation UNIX Workstation UNIX Workstation Comm. SW Comm. SW Comm. SW Comm. SW Net Inter. HW Net Inter. HW Net Inter. HW Net Inter. HW Fast Commercial Switch (Myrinet) NSF RI 99

14. Software Warehouse • Coherent software environment throughout the research program • Billions bytes of code • Mirrored externally • New SWW-NT NSF RI 99

15. Multi-Tier Networking Infrastructure • Myrinet Cluster Interconnect • ATM backbone • Switched Ethernet • Wireless NSF RI 99

16. Multimedia Development Support • Authoring tools • Presentation capabilities • Media stations • Multicast support / MBone NSF RI 99

17. Novel Cluster Designs • Tertiary Disk • very low cost massive storage • hosts archive of Museum of Fine Arts • Pleiades Clusters • functionally specialized storage and information servers • constant back-up and restore at large scale • NOW tore apart traditional AUSPEX servers • CLUMPS • cluster of SMPs with multiple NICs per node NSF RI 99

18. Massive Cheap Storage • Basic unit: 2 PCs double-ending four SCSI chains Currently serving Fine Art at http://www.thinker.org/imagebase/ NSF RI 99

19. Information Servers • Basic Storage Unit: • Ultra 2, 300 GB raid, 800 GB tape stacker, ATM • scalable backup/restore • Dedicated Info Servers • web, • security, • mail, … • VLANs project into dept. NSF RI 99

20. Cluster of SMPs (CLUMPS) • Four Sun E5000s • 8 processors • 3 Myricom NICs • Multiprocessor, Multi-NIC, Multi-Protocol NSF RI 99

21. Novel Systems Design • Virtual networks • integrate communication events into virtual memory system • Implicit Co-scheduling • cause local schedulers to co-schedule parallel computations using a two-phase spin-block and observing round-trip • Co-operative caching • access remote caches, rather than local disk, and enlarge global cache coverage by simple cooperation • Reactive Scalable I/O • Network virtual memory, fast sockets • ISAAC “active” security • Internet Server Architecture • TACC Proxy architecture NSF RI 99

22. Fast Communication • Fast communication on clusters is obtained through direct access to the network, as on MPPs • Challenge is make this general purpose • system implementation should not dictate how it can be used NSF RI 99

23. Virtual Networks • Endpoint abstracts the notion of “attached to the network” • Virtual network is a collection of endpoints that can name each other. • Many processes on a node can each have many endpoints, each with own protection domain. NSF RI 99

24. How are they managed? • How do you get direct hardware access for performance with a large space of logical resources? • Just like virtual memory • active portion of large logical space is bound to physical resources Host Memory Process n Processor *** Process 3 Process 2 Process 1 NIC Mem P Network Interface NSF RI 99

25. Network Interface Support • NIC has endpoint frames • Services active endpoints • Signals misses to driver • using a system endpont Frame 0 Transmit Receive Frame 7 EndPoint Miss NSF RI 99

26. Msg burst work Client Server Client Server Server Client Communication under Load => Use of networking resources adapts to demand. => VIA (or improvements on it) need to become widespread NSF RI 99

27. GS GS LS LS A A GS GS LS LS A A A A Implicit Coscheduling • Problem: parallel programs designed to run in parallel => huge slowdowns with local scheduling • gang scheduling is rigid, fault prone, and complex • Coordinate schedulers implicitly using the communication in the program • very easy to build, robust to component failures • inherently “service on-demand”, scalable • Local service component can evolve. NSF RI 99

28. WS 1 Job A sleep Job A request response WS 2 Job B Job A WS 3 Job B Job A spin WS 4 Job B Job A Why it works • Infer non-local state from local observations • React to maintain coordination observation implication action fast response partner scheduled spin delayed response partner not scheduled block NSF RI 99

29. I/O Lessons from NOW sort • Complete system on every node powerful basis for data intensive computing • complete disk sub-system • independent file systems • MMAP not read, MADVISE • full OS => threads • Remote I/O (with fast comm.) provides same bandwidth as local I/O. • I/O performance is very tempermental • variations in disk speeds • variations within a disk • variations in processing, interrupts, messaging, ... NSF RI 99

30. A D A A A A D D D D A D Distributed Queue A D A D Reactive I/O • Loosen data semantics • ex: unordered bag of records • Build flows from producers (eg. Disks) to consumers (eg. Summation) • Flow data to where it can be consumed Adaptive Parallel Aggregation Static Parallel Aggregation NSF RI 99

31. Performance Scaling • Allows more data to go to faster consumer NSF RI 99

32. Driving Applications • Inktomi Search Engine • World Record Disk-to_Disk store • RSA 40-bit key • IRAM simulations, Turbulence, AMR, Lin. Alg. • Parallel image processing • Protocol verification, Tempest, Bio, Global Climate. . . • Multimedia Work Drove Network Aware Transcoding Services on Demand • Parallel Software-only Video Effects • TACC (transcoding) Proxy • Transcend • Wingman • MBONE media gateway NSF RI 99

33. Transcend Transcoding Proxy • Application provides services to clients • Grows/Shrinks according to demand, availability, and faults Service request Front-end service threads User Profile Database Manager Physical processor Caches NSF RI 99

34. UCB CSCW Class Sigh… no multicast, no bandwidth, no CSCW class... Problem Enable heterogeneous sets of participants to seamlessly join MBone sessions. NSF RI 99

35. A Solution: Media Gateways • Software agents that enable local processing (e.g. transcoding) and forwarding of source streams. • Offer the isolation of a local rate-controller for each source stream. • Controlling bandwidth allocation and format conversion to each source prevents link saturation and accommodates heterogeneity. GW GW NSF RI 99

36. A Solution: Media Gateways Sigh… no multicast, no bandwidth, no MBone... AHA! MBone Media GW NSF RI 99

37. FIAT LUX: Bringing it all together • Combines • Image Based Modeling and Rendering, • Image Based Lighting, • Dynamics Simulation and • Global Illumination in a completely novel fashion to achieve unprecedented levels of scientific accuracy and realism • Computing Requirements • 15 Days of worth of time for development. • 5 Days for rendering Final piece. • 4 Days for rendering in HDTV resolution on 140 Processors • Storage • 72,000 Frames, 108 Gigabytes of storage • 7.2 Gigs after motion blur • 500 MB JPEG • premiere at the SIGGRAPH 99 Electronic Theater • http://fiatlux.berkeley.edu/ NSF RI 99