1. 1 CSSE 477 – Intro to Performance Steve Chenoweth Friday, 9/2/11 Week 0, Day 2 Right – A close analogy to performance as we mean it – Danica Patrick in an Andretti Honda at the Indy 500, 2007. From http://www.zimbio.com/pictures/jMc7rq1aK8 x/91st+Indianapolis+500/0nC_oFFbsHj/Dani ca+Patrick. http://www.zimbio.com/pictures/jMc7rq1aK8 x/91st+Indianapolis+500/0nC_oFFbsHj/Dani ca+Patrick

2. 2 Today Finalize who’s on what team / project How to do Project 1… Which is all about software performance engineering… –Bass’s Ch 4 (pp 82-85) and Ch 4 (pp 111- 116) –For a whole lot more, see Performance Solutions: A Practical Guide to Creating Responsive, Scalable Software, by Connie Smith and Lloyd Williams

3. 3 Yesterday, we picked performance from Bass’s QA list… Bass’s list of six, from the inside back cover of his book: –Availability –Modifiability –Performance –Security –Testability –Usability

4. 4 And you got a first project about it: On the project you selected to work on, Improve the performance by 100%. And a first step to take: Decide what “Improve the performance by 100%” means.

5. 5 With luck… You picked something you could measure! Which, as we’ll see on all the QA’s… Is why Bass writes down “scenarios” with measurable responses, as his arch targets We’ll cover these systematically in Ch 4 See also “The Notes” at the end of the supplementary spec template. supplementary spec template

6. 6 Bass’s perf scenarios Source: One of a number of independent sources, possibly from within system Stimulus: Periodic events arrive; sporadic events arrive; stochastic events arrive Artifact: System Environment: Normal mode; overload mode Response: Processes stimuli; changes level of service Response Measure: Latency, deadline, throughput, jitter, miss rate, data loss

7. 7 Example scenario Source: Users Stimulus: Initiate transactions Artifact: System Environment: Under normal operations Response: Transactions are processed Response Measure: With average latency of two seconds

8. 8 So if you need to fix yours up… Find a “doable” performance improvement Whose starting state can be characterized as one of those scenarios!

9. 9 What do you do next? Adopt a tactic or two… –Ch 5 in Bass has these –But they are deceptively brief –Each area – like designing high performance into a system – could be your career! What on earth could improve performance by 100%?

10. 10 The tactics for performance Mostly, they have to work like this (Fig. 5.6): Tactics to control performance Events arrive Responses generated within time constraints

11. 11 Typically… The events arrive, but Some reasons can be ID’ed for their slow processing Two basic contributors to this problem: 1.Resource consumption – the time it takes to do all the processing to create the response 2.Blocked time – it has to wait for something else to go first

12. 12 Which one’s easier to fix? Blocked time – sounds like it could lead pretty directly to some solution ideas, like: –Work queues are building up, so add more resources and distribute the load, or –Pick the higher priority things out of the queue, and do them first

13. 13 Blocked time, cntd In your system, of course, adding resources may or may not be possible! –Add disk drives? –Add CPU’s? –Speed up communication paths? On servers, these are standard solutions: –Put every DB table on its own disk drive –Stick another blade in the rack, etc.

14. 14 Resource consumption? You first have to know where it is: If you’re trying to speed up a GUI activity, time the parts, and go after the long ones. If it’s internal, you need some way to “observe” what’s happening, so you can do a similar analysis. –Put timings into the various pieces of activity –Some parts may be tough to break down, like time spent in the O/S

15. 15 Performance Engineering with a Spreadsheet Typical new system design analysis – For a network management system Note: Having everything add up to only 60% allows for some “blocked time” Note: These are all resource consumption estimates

16. 16 Performance Engineering with a Spreadsheet Typical existing system performance-improvement analysis – To improve a customer help desk system Activity Current clock time (sec) Current elapsed time Proposed new ETNew clock timeNotes 0 0 Wait between calls18 12 To allow for peaks Take next call235517Operator response time Greet customer3815 32 Loop - repeat factor:Each cycle:21.5Each cycle:Retries of the next steps Get nature of problem30 15 Includes questioning Analyze4515 30Mostly think time Propose solution6520 50Mostly explaining steps Customer tries solution8520 70Widest variance here Each loop total:85 70 End of last loop:208 137 Close-out call21810 147Thank you, etc. Write-up call24830 177Documentation Total savings : 71sec Improvement : 40%

17. 17 Bass’s Performance Remedies Try one of these 3 Strategies – look at: –Resource demand –Resource management –Resource arbitration See next slides for details on each  –They’re also summarized on the inside back cover of Bass’s book, pp. 111-116

18. 18 Resource Demand – example: Server system has “the database” for retail inventory (for CSSE 374’s NextGen POS): –Transactions hit it at a high rate, from POS –Managers also periodically do huge queries, like, “What toothpaste is selling best West of the Mississippi?” –When they do, transactions back up How to fix?

19. 19 Resource Demand – options: Increase computational efficiency Reduce computational overhead Manage event rate Control frequency of sampling Bound execution times Bound queue sizes

20. 20 Resource Management – example: You have a “pipe and filter” system to convert some data for later processing: It runs too slowly, because it reads and writes all files on the same disk (on your laptop, say) How to fix? Picture from http://www.dossier-andreas.net/software_architecture/pipe_and_filter.html.http://www.dossier-andreas.net/software_architecture/pipe_and_filter.html Non-XML data from outside XML data you can process Clean up Convert

21. 21 Resource Management – options: Introduce concurrency –How about on your project? Maintain multiple copies of data or computations Increase available resources

22. 22 Resource Arbitration – example: In reader / writer scheduling… For a shared resource, like a DB table… Why give priority to the readers?

23. 23 Resource Arbitration – options: Scheduling policy –FIFO –Fixed-priority semantic importance deadline monotonic rate monotonic –Dynamic priority –Static scheduling

24. 24 Cartoon of the Day (1/2)

25. 25 Cartoon of the Day (2/2)

26. 26 Back to Project 1… Project 1 - review: On the team and project you picked, your first goal is to: Improve the performance by 100%. We’ll have presentations / demos next week. They should be convincing! Show before and after.

27. 27 What to do next? Get with your teammate(s) and 1.If you are still deciding the things that are due to be turned in tonight (Turnin 1), work on those! Like writing up what the project is, or the performance goals you want to try for. 2.Do a quantitative analysis of your situation and proposed improvement, on a spreadsheet –Like slide 16 3.Revise your goal, if necessary… –It should be testable – A week from today! 4.Pick a tactic, to try for the 100% improvement. Capture your discussion in your “team journal” (by adding a new entry – include your revised goal, your tactic, and how you arrived at each of these) Over the weekend – work with your team! Turnin 2 - Turn in your spreadsheet and journal on Angel by the end of the day on Monday –Should discuss all 3 of Bass’s “tactics” –Should explain HOW you plan to use one