Optimal Real-Time Database Management

1. Optimal Real-Time Database Management IEEE SoutheastCon 2008 April 5, 2008

2. The ATC system presented in this paper could reduce airline costs by $6 Billion per year Based on saving 5 minutes/flight, 20gals/minute and75,000 flights/day.

3. Dr. Frederick P. Brooks, leader of IBM 360 system software development, in the 1995 edition of his book entitled “The Mythical Man-month", (after cancellation of AAS, started in 1981) offers: "No scene from prehistory is quite so vivid as that of the mortal struggles of great beasts in the tar pits. In the mind's eye one sees dinosaurs, mammoths and saber-toothed tigers struggling against the grip of the tar. The fiercer they struggle, the more entangling the tar, and no beast is so strong or so skillful but that he ultimately sinks.

4. LaBrea Tar Pits

5. "Large-system programming has over the last decade been such a tar pit, and many great and powerful beasts have thrashed violently in it. Most have emerged with running systems—few have met goals, schedules, and budgets. Large and small, massive or wiry, team after team has become entangled in the tar. No one thing seems to cause the difficulty—any particular paw can be pulled away. But the accumulation of simultaneous and interacting factors brings slower and slower motion. Everyone seems to have been surprised by the stickiness of the problem, and it is hard to discern the nature of it. But we must try to understand it if we are to solve it."

6. Multiprocessor Programming Problems That Cause the “Stuck in the Tar Pits” Syndrome            Multi-tasking and multi-thread software            Shared resource management          Coherency management (memory, cache)            Preemption management          Priority inversion handling          Table/record/item data locking Individual processor state evaluation Task assignment to processor            Data broadcast and Reduction of results            Maintaining serializability       Data sorting and indexing          Data link/pointer management          Resorting/re-indexing as data changes       Lock management

7. Bradley’s bromide shows another way to get to the “tar pits”. “If computers get too powerful – we can organize them into a committee – that will do them in.” There is a way around the "tar pits." That's the purpose of this paper. The solution: Permit only one instruction to act on the ATC database at any time First, let’s take a quick look at past ATC efforts.

8. ATC History 1963 .… -1963 ATC CCC Spec not met –has not been met to date. System in use through ’70s. Couldn’t repair (couldn’t get vacuum tubes). Replaced with IBM hardware – Called “Host” Performance improvement?? -1973 DABS/IPC Excellent system approach. Development awarded to TI $25M+ TI wrote spec – didn’t bid - program died -1981 AAS - 2 proof of performance contracts ~ $500Meach No proof. Contracts stopped. Theorists say it’s an intractable problem. Theory proven by contractors. -1983 Without proof - AAS contract to IBM ~ $8B By 1994 system had 185 processors – way over budget -- unmanageable software. Canceled June ’94 -1994 STARS came into development – the terminal subset of AAS. Installation late. Many questions by GAO. Now up.

9. Computer Complexity 1. Conceptual 2. Algorithmic 3. Time 4. Space Most evaluation is done using Time complexity

10. Real-Time Computer Complexity Theory John Stankovic; “…complexity results show that most real-time multiprocessor scheduling is NP-hard.” Mark Klein; “…most realistic problems incorporating practical issues … are NP-hard.” Garey, Graham and Johnson; “…all but a few schedule optimization problems are considered insoluble… For these [insoluble] scheduling problems, no efficient optimization algorithm has been found, and indeed, none is expected.” and “…most scheduling problems belong to the infamous class of NP-complete problems.”

11. NP-hard and NP-complete strongly imply that predictable scheduling cannot be implemented. After 34 years of experimentation and having spent over 50 billion dollars, predictable scheduling has not been demonstrated for ATC Multiprocessors.

12. The AP is a better way to do the ATC job It uses a different, much simpler, more easily programmed, highly parallel computer system But first –What’s wrong with the present Multiprocessor System? Let’s look at computer complexity

13. The Associative processor (AP) was demonstrated at Knoxville in 1971, at Dulles in 1972 and was used by USN starting in 1978. The AP could have satisfied all requirements on the previous slide. It can meet today’s requirements and can automatically provide many General Aviation advisories such as restricted areas, nearby aircraft, unsafe terrain ahead, etc. The AP can meet ATC and NGATS needs. Let’s start NOW!

14. What is the Time Complexity Function (TCF)? Garey and Johnson write: “… Think in terms of time complexity as determined from the corresponding operand input lengths and execution times.” In the AP– input lengths are not significant; think only of execution times Let’s Compare the AP and the MP

15. Number of operands n 10 20 30 40 50 60 Time Complexity Function (Time in microseconds) O(n) O(1) in AP O(n2) O(n) in AP O(n3) O(n2) in AP 10 20 30 40 50 60 1 1 1 1 1 1 100 400 900 1600 2500 3600 10 20 30 40 50 60 1000 8000 27000 64000 250000 216000 100 400 900 1600 2500 3600 Table from Computers and Intractability, A Guide to the Theory of NP-Completeness, Garey and Johnson, 1979; Fig 1.2, Page7. AP processing times added.

16. Dr. JohnStankovic writes: “Real-time solutions must have four attributes: speed, predictability, adaptability and reliability.” We agree: Satisfactory performance demands predictability. Today all significant multiprocessor scheduling must use a dynamic or heuristic approach. These approaches have been found to be unpredictable, and resulting solutions are considered NP-hard, NP-complete or intractable. A good reason to: Use an Associative Processor

17. Multiprocessor task scheduling Task i b d t a t Other Tasks c t 0 t Many Instructions at a Time Tasks starting at a and c must precede task starting at b. OK here.

18. Multiprocessor task intersection Task i b d t a t Other Tasks c t 0 t Many Instructions at a Time Task starting at b has exceeded deadline time -------------------------------------------------------------------------------------------------------- In Associative Processor task separation AP All Tasks 0 t One Instruction at a time All tasks start at scheduled time

19. Associative Processor (AP) An AP simultaneously processes thousands of operands (one operand per PE) with each instruction. An AP provides fully predictable scheduling that is unachievable with a multiprocessor Real-time AEW Experience shows 276 times greater throughput than a dual processor (When ignoring deadline time in the dual processor).

20. Associative Processor (AP) (cont) Much simpler instructions: e.g. one instruction, ADF(a,b,c) states: add field ai to field bi and store the result in field ci (for each of thousands of records). All records are treated at the same time with that one instruction - executed once. Of even greater significance is the elimination of a great many program steps that are absolutely essential to the multiprocessor operations. What are some of the steps eliminated?

22. Multiprocessor Programming Problems That Do Not Exist In The Associative Processor            Multi-tasking and multi-thread software            Shared resource management          Coherency management (memory, cache)            Preemption management          Priority inversion handling          Table/record/item data locking Individual processor state evaluation Task assignment to processor            Data broadcast and Reduction of results            Maintaining serializability       Data sorting and indexing          Data link/pointer management          Resorting/re-indexing as data changes       Lock management

23. All the operations on the previous slide, while indispensable to the multiprocessor,Are unnecessary in the single instruction stream software system of the Associative Processor

24. Go to a new starting point,theAP is: To Solve the ATC Problem! A parallel processing technique that can processa set operands, with a single instruction. Let’s compare MP and AP computational systems Each computer in a MP has an instruction processor (IP) and a processing element (PE). Each IP gets instructions and manages its own PE. The AP, a set processor, has one IP that simultaneously manages thousands of PEs. A single AP instruction can simultaneously produce thousands of results.

25. Processor organizations von Neumann Processor Data and Instruction memory I/O unit PE Instruction Processor Data memory PE Data memory PE Associative Processor 16,381 more Data memory PE I/O unit Instruction Processor Instruction Memory What is the ATC Problem?

26. Air Traffic Control:A Real-Time Database problem (RTDB) A prime requisite of the ATC system is to Automatically develop and maintain a track for every aircraft providing its position and velocity at all times. Current ATC automation cannot accomplish this simple task. Current systems cannot automatically develop and maintain tracks for every aircraft at all times.

27. To Manage a RTDB System use anAssociative Processor Implemented in Knoxville, 1971 STARAN - demonstrated at Dulles, 1972 AEW - Operational in the USN E2C Hawkeye Aircraft, 1983

28. Knoxville Terminal 1971 Automatically initiate tracking on all primary and secondary radar and provide: Conflict detection, Conflict resolution, Terrain avoidance, Automatic voice advisory. What was done at Knoxville in 1971 cannot be done in any of today’s ATC systems.

29. STARAN at Dulles Expo –1972 Automatically initiated tracking on all primary and secondary radar, and provided: Conflict detection Conflict resolution Terrain avoidance Automatic voice advisory Display processing Flight plan processing Flight plan simulation Simulated processing - 7,500 flights per 10 second radar scan time.

30. USN ASPRO 1977 Initial Design 1983 Delivery to fleet E2C Characteristics …Space < .5 cu. ft. (including power supply and backup battery) …< 250 watts power Performance …276 times more than the on board dual processor (ignoring time in dual)

31. ASPRO

32. Each board in the previous slide had 384 processors and 4096 bits of memory per processor. There were a total of 2112processors in ASPRO in a 9” x 9” x 9” space. Let’s look at performance!

34. ASPRO Predictability -- Simulated environment 4,000 Reports – 2,000 Tracks Routine Instruction Time in milliseconds/scan count Predicted Measured Association pairing 415 * 640.0 Compare and sort 1012 * 14.0 Correlation 788 22.16 4.5 Tentative Track 555 16.68 12.5 Track Update 661 14.84 8.9 Hghtup 407 2.68 2.9 Range Prediction 640 37.04 24.77 Association gates 443 9.12 8.0 Kalman Tracking 1026 46.64 39.2 Track Quality 209 7.28 5.06 Air/Surface 326 * 0.66 Establish Track 407 0.88 0.71 Final Bookkeeping 243 15.98 6.6 ----------------------------------------------------------------------------------------- Totals 7132 767.8 msec * not predicted 113.14 msec for ATC tracking The L304 Processor took 212 seconds for same jobs

35. Improving theUS ATC System -An Updated ASPRO could: (While saving Billions of dollars) have satisfied all requirements for AAS in 50% of available real time, added more functional performance, exceeded failsafe requirements and reduced software cost by at least 80%

37. Let’s look at a near termATC Center Environment IFR flights 4,000 VFR/backup flights 10,000 Controllers 600 Sensor Reports per second 12,000 How would an AP predict performance?.

38. Table 1. ATC Tasks – Worst Case Environment Task Transactions/sec p j*10-6c Processing Time 1.        Report Correlation & Tracking 12,000 .5 15 .09 1.6 2.        Cockpit Display 750 1.0 120 .09 .8 3.       Controller Display Update 7,500 1.0 12 .09 .8 4.        Aperiodic Requests 200 1.0 250 .05 .48 5.        Automatic Voice Advisory 150 4.0 75 .18 .38 6.        Terrain Avoidance 1,000 8.0 40 .32 .33 7.        Conflict Detection & Resolution 750 4.0 60 .36 .38 8.        Final Approach (100 runways) 750 8.0 33 .2 .21 - Major Period P Sum: Transactions 168,350 Total time sec 4.98 P is an 8 second major period in which all tasks must be completed, p is each tasks period in seconds, j is the execution time for each job in a task, Each task is a set of jobs, c is the cost for each task for the worst-case set of jobs, each task = (c + .01) (includes 10 msec interrupt time per task) Proc. Time = P*(c+.01)/p

39. A single instruction AP can meet current ATC and NexGen needs. A multiple instruction MP cannot! Let’s move forward!

40. Acronyms AAS – All Application Air Traffic Automation System AEW – Airborne Early Warning System CCC – Central Computer Complex NAS (Enroute) DABS/IPC – Discrete Addressable Bacon System/Intermittent Positive Control PE – Processing Element