what every web and app developer should know about multithreading

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  • By-nc-nd 2.0 Clemens Schwaighofer http://flickr.com/photos/gullevek/257135337/ Introduction to threading Time for questions at the end; if it’s really brief, interrupt me

Transcript

  • 1. what every web and app developer should know about multithreading
  • 2. why
  • 3. why
    • On the desktop, one core is rarely enough
    • On the web, sometimes we need parallel execution
    • Performance requires caching
    • Persistence of connectivity requires responsiveness
    • Disk and network I/O is indispensible and v ery slow
  • 4. threads
    • A way to execute two things at once
  • 5. threads
    • A way to execute two things almost at once
    • Lightweight
    • Independent execution
    • Almost like a separate process
  • 6. thread process versus
  • 7. thread
    • A process is isolated in memory
    • When it dies, its memory is released
    • When it dies, its threads die too
    • Somewhat difficult to talk to other processes
    versus
  • 8.
    • All threads in a process share memory
    • Can be started and stopped as needed
    • On some platforms, cheaper to launch than a process
    • Can be native (kernel-based) or user-mode
    process versus
  • 9. threads
  • 10. threads
    • Less predictable execution
    • Must control for re-entrancy of code
    • Must be aware of shared data
    • More difficult than it seems
  • 11. synchronization
    • We must retain predictability in our programs
    • Two threads fighting for the same variable
    Thread A my_local_x = x set x = my_local_x + 1 Thread B my_local_x = x set x = my_local_x + 2
  • 12. synchronization
    • We must retain predictability in our programs
    • Two threads fighting for the same variable
    Thread A my_local_x = x set x = my_local_x + 1 Thread B my_local_x = x set x = my_local_x + 2
    • If we started out with x = 2, we end up with x = 5
  • 13. synchronization
    • We must retain predictability in our programs
    • Two threads fighting for the same variable
    Thread A my_local_x = x set x = my_local_x + 1 Thread B my_local_x = x set x = my_local_x + 2
    • If we started out with x = 2, we end up with x = 5
  • 14. synchronization
    • We must retain predictability in our programs
    • Two threads fighting for the same variable
    Thread A my_local_x = x set x = my_local_x + 1 Thread B my_local_x = x set x = my_local_x + 2
    • If we started out with x = 2, we end up with x = 4
  • 15. synchronization
    • First rule of synchronization: avoid needing it
    • Thread-local storage
    • Function scope variables
    • No side effects
    • Functional languages
    list.sort()
  • 16. synchronization
    • First rule of synchronization: avoid needing it
    • Thread-local storage
    • Function scope variables
    • No side effects
    • Functional languages
    list.sort() newlist = list.sort()
  • 17. synchronization
    • Second rule of synchronization: join threads
    • Use a worker thread
    • Join – wait for it to finish, then read its results
  • 18. synchronization Thread A Thread B Main Thread Start A Start B Join A and B Read data
  • 19. synchronization
    • Third rule of synchronization: go critical
    • Declare a critical section
    • You are alone within your application…
    • … until you end the critical section
    • Application-wide setting
    • Hard to use when you have a bunch of threads
  • 20. synchronization
    • Third rule of synchronization: mutual exclusion
  • 21. synchronization
    • Third rule of synchronization: mut ual ex clusion
  • 22. synchronization
    • Third rule of synchronization: mutex
    • Allows you to “lock” and “unlock” resources
    • Like an object for a mini-critical section
    • Thread A
    • lock M
      • my_local_x = x
      • set x = my_local_x + 1
    • unlock M
    • Thread B
    • lock M
      • my_local_x = x
      • set x = my_local_x + 1
    • unlock M
  • 23. synchronization
    • Third rule of synchronization: use a semaphore
    • Like a mutex, but lets more than one thread through
    • Mutex with a counter
    • Checks availability, then “acquires” one count
    • When done, “releases” one count, unblocking others
  • 24. synchronization
    • Synchronization is about blocking
    • Allows you to control access to code and data
    • Protects areas of code that shouldn’t be left to chance
  • 25. examples
    • Worker threads
    • Thread pools
    • Producer / Consumer
    • Cache
    • Will use .NET for examples
  • 26. example
  • 27. example
  • 28. example
  • 29. example
  • 30. bad threading
  • 31. bad threading
    • It is simple when simple, and fiendish when complex
    • Watch out for race conditions: lock often to prevent
    • Watch for deadlocks: don’t lock too much
    • Watch for incomplete locks: lock carefully
  • 32. bad threading
    • Lock for the smallest amount of time
    • If possible, lock for consistency…
    • … then copy the data and use it locally
    • Instead of blocking on locks, wait with a timeout
    • Use lots of debug logging if you’re in trouble
  • 33. photo credits CC BY-NC-ND 2.0 – Clemens Schwaighofer – http://flickr.com/photos/gullevek/257135337/ CC BY-NC-SA 2.0 – Robert Parviainen – http://flickr.com/photos/rtv/2574427997/ CC BY-NC-ND 2.0 – Sudhir Srinivasa – http://flickr.com/photos/sudhirs/111760673/ CC BY-NC-SA 2.0 – Rick Harrison – http://flickr.com/photos/sovietuk/2657691123/ CC BY-NC-ND 2.0 – Joe Chiapputo – http://flickr.com/photos/cocoabeachjoe/1924133031/ CC BY-ND 2.0 – Craig Allen – http://flickr.com/photos/anabadili/2759448841/