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THsort PennySort Award Ceremony Beijing China 19 October 2002

THsort PennySort Award Ceremony Beijing China 19 October 2002. Peng Liu , Yao Shi , Li Zhang , Kuo Zhang , Tian Wang , | ZunChong Tian , Hao Wang , Xiaoge Wang Trophy presentation by Jim Gray. Outline. Penny Sort history and Award The need for long-range research

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THsort PennySort Award Ceremony Beijing China 19 October 2002

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  1. THsort PennySort Award CeremonyBeijing China19 October 2002 Peng Liu, Yao Shi, Li Zhang, Kuo Zhang, Tian Wang, |ZunChong Tian, Hao Wang, Xiaoge Wang Trophy presentation by Jim Gray

  2. Outline • Penny Sort history and Award • The need for long-range research • Some long-range systems research goals. • What I have been doing.

  3. Benchmark History 1970 IBM TP 1-7CA and Tony Lukes Debit Credit Gray 1980 Wisconsin Bitton Boral DeWitt Turbyfill Datamation Anon et al Sort MCC Boral &... Teradata Bollinger &... TPC-A 1990 TPC-B TPC-C PennySort MinuteSort TPC-D TPC-W ? 2000

  4. A Short History of Sort • April Fools 1995: Datamation Sort • Sort 1M 100 B records • An IO benchmark: 15-min to 1 hr! • 1993: {Minute | Penny}x{Daytona | Indy} • 1998: TeraByte Sort • Web site: http://research.Microsoft.com/barc/SortBenchmark/

  5. Ground Rules • How much can you sort for a penny (in a minute). • Hardware and Software cost • Depreciated over 3 years • 1M$ system gets about 1 second, • 1K$ system gets about 1,000 seconds. • Time (seconds) = SystemPrice ($) / 946,080 • Input and output are disk resident • Input is • 100-byte records (random data) • key is first 10 bytes. • Must create output file and fill with sorted version of input file. • Daytona (product) and Indy (special) categories

  6. PennySort • Hardware • 266 Mhz Intel PPro • 64 MB SDRAM (10ns) • Dual Fujitsu DMA 3.2GB EIDE disks • Software • NT workstation 4.3 • NT 5 sort • Performance • sort 15 M 100-byte records (~1.5 GB) • Disk to disk • elapsed time 820 sec • cpu time = 404 sec

  7. 1999 PennySort • Daytona & Indy:2.58 GB in 917 sec • HMsort: Brad Helmkamp, Keith McCready, Stenograph LLC • Intel 400Mhz2 IDE disks

  8. 1998 TB Sort • Chris NybergNsortSGI 32x Origin2000151 Minutes

  9. 1999 Terabyte Sort • Daytona:Daivd Cossock, Sam Fineberg,Pankaj Mehra, John PeckTandem/Sandia TSort: 68 CPU ServerNet47 minutes • Indy:IBM SPsort 408 nodes, 1952 cpu 2168 disks 17.6 minutes = 1057sec (all for 1/3 of 94M$, slice price is 64k$ for 4cpu, 2GB ram, 6 9GB disks + interconnect

  10. SP sort • 2 – 4 GBps!

  11. 2002 Sort Records Daytona Indy Penny 9.8 GB 1098 seconds 105 million records $857 Linux/Intel THsort, report as doc (128KB) or pdf (33KB)Peng Liu, Yao Shi, Li Zhang, Kuo Zhang, Tian Wang, ZunChong Tian, Hao Wang, Xiaoge WangHigh Performance Institute, Dept. of Computer Science and Technology, Tsinghua University, Beijing 100084, China 11.6 GB 1380 seconds 125 m records on a $672 Linux/Intel systemDMsortpdf (660KB), ps(950KB) Araron Darling, Alex Mohr,U. Wisconsin, Madison Minute 12 GB in 60 secondsOrdinal NsortSGI 32 cpu Origin IRIX 21.8 GB in 56.51 sec 218 million recordsNOW+HPVMsort 64 nodes WinNT pdf.Luis Rivera , Andrew Chien UCSD TeraByte 49 minutes Daivd Cossock, Sam Fineberg,Pankaj Mehra, John Peck68x2 Compaq &Sandia Labs 1057 secondsSPsort 1952 SP cluster 2168 disks Jm WylliePDF SPsort.pdf (80KB) 1999 Sort Records

  12. The THsort Team(and friend)

  13. 2x/year! • Partly hardware • Partly software • Partly economics THsort ~ 1TB/$

  14. Progress on Sorting • Speedup comes from Moore’s law 40%/year • Processor/Disk/Network arrays: 60%/year (this is a software speedup). THsort ~1TB/$

  15. Musings: PennySort=TBsort • Sorts 1TB in 1Minute • 2 pass so 3TB of disk • = 10 disks if 330GB/disk • = 5Gps (if each disk is 50Mbps) • So, 600 seconds (3TB/5GBps) • So, node costs 1.5k$ • Costs 100x that today • maybe in 4 years?

  16. Outline • Penny Sort history and Award • The need for long-range research • Some long-range systems research goals. • What I have been doing.

  17. Properties of a Research Goal • Simple to state. • Not obvious how to do it. • Clear benefit. • Can be broken into smaller steps • So that you can see intermediate progress. • Progress and solution is testable.

  18. I was motivated by a simple goal scaleup: 1,000,000 : 1 • Devise an architecture that scales up: Grow the system without limits*. This is impossible (without limits?), but...This meant automatic parallelism, automatic management, distributed, fault tolerant, high performance • Benefits: • long term vision guides research problems • simple to state, so attracts colleagues and support • Can tell your friends & family what it is that you do .

  19. Three Seminal Papers • Babbage: Computers • Bush: Automatic Information storage & access • Turing: Intelligent Machines • Note: • Previous Turing lectures described several “theory” problems. • Problems here are “systems” problems. • Some include a “and prove it” clause. • They are enabling technologies, not applications. • Newell’s: Intelligent Universe (Ubiquitous computing.) missing because I could not find “simple-to-state” problems.

  20. Charles Babbage(1791-1871) • Babbage’s computing goals have been realized • But we still need better algorithms & faster machines • What happens when • Computers are free and infinitely powerful? • Bandwidth and storage is free and infinite? • Remaining limits: • Content: the core asset of cyberspace • Software: Bugs, >100$ per line of code (!) • Operations: > 1,000 $/node/year

  21. 1890-1945 Mechanical Relay 7-year doubling 1945-1985 Tube, transistor,.. 2.3 year doubling 1985-2000 Microprocessor 1.0 year doubling ops/s/$ Had Three Growth Curves 1890-1990 Combination of Hans Moravac + Larry Roberts + Gordon Bell WordSize*ops/s/sysprice

  22. Trouble-Free Appliances • Appliance just works. TV, PDA, desktop, ... • State replicated in safe place (somewhere else) • If hardware fails, or is lost or stolen, replacement arrives next day (plug&play). • If software faults, software and state refresh from server. • If you buy a new appliance, it plugs in and refreshes from the server (as though the old one failed) • Most vendors are building towards this vision. • Browsers come close to working this way.

  23. Trouble-Free Systems • Manager • Sets goals • Sets policy • Sets budget • System does the rest. • Everyone is a CIO (Chief Information Officer) • Build a system • used by millions of people each day • Administered and managed by a ½ time person. • On hardware fault, order replacement part • On overload, order additional equipment • Upgrade hardware and software automatically.

  24. Trustworthy Systems • Build a system used by millions of people that • Only services authorized users • Service cannot be denied (can’t destroy data or power). • Information cannot be stolen. • Is always available: (out less than 1 second per 100 years = 8 9’s of availability) • 1950’s 90% availability, Today 99% uptime for web sites, 99.99% for well managed sites (50 minutes/year)3 extra 9s in 45 years. • Goal: 5 more 9s: 1 second per century. • And prove it.

  25. 20 $ to design and write it. 30 $ to test and document it. 50 $ to maintain it. 100$ total The only thing in Cyber Space that is getting MORE expensive & LESS reliable 100 $ line of code?1 bug per thousand lines? • Solution so far: • Write fewer lines High level languages • Non Procedural • 10x not 1,000x better Very domain specific • Application generators: • Web sites, Databases, ... • Semi-custom apps: • SAP, PeopleSoft,.. • Scripting & Objects • JavaScript & DOM

  26. Automatic ProgrammingDo What I Mean (not 100$ Line of code!, no programming bugs)The holy grail of programming languages & systems • Devise a specification language or UI • That is easy for people to express designs (1,000x easier), • That computers can compile, and • That can describe all applications (is complete). • System should “reason” about application • Ask about exception cases. • Ask about incomplete specification. • But not be onerous. • This already exists in domain-specific areas. (i.e. 2 out of 3 already exists) • An imitation game for a programming staff.

  27. Outline • Penny Sort history and Award • The need for long-range research • Some long-range systems research goals. • What I have been doing.

  28. What I Have Been Doing • Traveling & Talking • Helping Alex Build the SkyServer • Loading data • Helping build the Virtual Observatory • Doing spatial geometry in SQL (no kidding)! • Learning about web services (and implementing some)

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