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High Performance Erlang

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High Performance Erlang

  1. 1. Erlang and Scalability Percona Performance 2009 Jan Henry Nystrom henry@erlang-consulting.com 2007 Course Introduction Course Title @ Course Author
  2. 2. Introduction • Scalability Killers • Design Decisions – Language and Yours • Thinking Scalable/Parallel • Code for the correct case • Rules of Thumb • Scalability in the small: SMP Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 2
  3. 3. Scalability Killers • Synchronization • Resource contention Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 3
  4. 4. Scalability Killers • Synchronization Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 3
  5. 5. Design Decisions No sharing • Processes • Encapsulation • No implicit synchronization Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 4
  6. 6. Design Decisions No implicit synchronization • Spawn always succeed • Sending always succeed • Random access message buffer • Fire and forget unless you need the synchronization Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 5
  7. 7. Design Decisions Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  8. 8. Design Decisions Concurrency oriented programming Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  9. 9. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  10. 10. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  11. 11. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  12. 12. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  13. 13. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case • Clear Code Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  14. 14. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case • Clear Code Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  15. 15. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case • Clear Code Clarity is King! Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  16. 16. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case • Clear Code Clarity is King! Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  17. 17. Design Decisions Concurrency oriented programming • Concurrency support an integral part of the language • Distribution support • Sets the focus firmly on the concurrent tasks • Code for the correct case • Clear Code Clarity is King! I rather try to get clear code correct than correct code clear Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 6
  18. 18. Thinking Scalable/Parallel 0 Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 7
  19. 19. Thinking Scalable/Parallel List length: Obviously Linear 4: But not when you have n processors? Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 7
  20. 20. Thinking Scalable/Parallel List length: O(logN) with sufficient processors Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 8
  21. 21. Thinking Scalable/Parallel List length: O(logN) with sufficient processors 4 2 2 1 1 1 1 Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 8
  22. 22. Thinking Scalable/Parallel In the Erlang setting • Do not introduce unneeded synchronization • Remember processes are cheap • Do not introduce unneeded synchronization • A terminated process is all garbage • Do not introduce unneeded synchronization Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 9
  23. 23. Code for the Correct Case Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 10
  24. 24. Code for the Correct Case request set timer request set timer request set timer Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 10
  25. 25. Code for the Correct Case request set timer request set timer request set timer r answe release timer check r answe release timer check er answ release timer check Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 10
  26. 26. Code for the Correct Case request set timer request set timer request set timer r answe release timer check r answe release timer check er answ release timer check Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 10
  27. 27. Code for the Correct Case Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 11
  28. 28. Code for the Correct Case request set timer request request Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 11
  29. 29. Code for the Correct Case request set timer request request nswer a Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 11
  30. 30. Rules of Thumb • Rule 1 - All independent tasks should be processes • Rule 2 - Do not invent concurrency that is not there! f() g() h() Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 12
  31. 31. Rules of Thumb • Rule 1 - All independent tasks should be processes • Rule 2 - Do not invent concurrency that is not there! f() g() h() Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 12
  32. 32. Rules of Thumb • Rule 1 - All independent tasks should be processes • Rule 2 - Do not invent concurrency that is not there! f() g() h(g(f())) h() Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 12
  33. 33. Rules of Thumb • Rule 1 - All independent tasks should be processes • Rule 2 - Do not invent concurrency that is not there! f() g() h(g(f())) h(g(f())) h(g(f())) h(g(f())) h() Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 12
  34. 34. Scalability in the small: SMP Erlang SMP ”Credo” SMP should be transparent to the programmer in much the same way as Erlang Distribution • You shouldn’t have to think about it ...but sometimes you must • Use SMP mainly for stuff that you’d make concurrent anyway • Erlang uses concurrency as a structuring principle • Model for the natural concurrency in your problem Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 13
  35. 35. Scalability in the small: SMP ”Big bang” benchmark on Sunfire T2000 • Erlang on multicore 1 scheduler • SMP prototype ‘97, First OTP release May ‘06. • Mid -06 benchmark mimicking call handling (axdmark) on the (experimental) SMP emulator. Observed speedup/core: 0.95 • First Ericsson product (TGC) released on SMP Erlang in Q207. 16 schedulers Simultaneous processes Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 14
  36. 36. Scalability in the small: SMP Case Study: Telephony Gateway Controller AXE TGC • Mediates between legacy telephony and multimedia networks. • Hugely complex state machines GW GW GW • + massive concurrency. • Developed in Erlang. • Multicore version shipped to customer Q207. • Porting from 1-core PPC to 2-core Intel took < 1 man-year (including testing). Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 15
  37. 37. Scalability in the small: SMP Case Study: Telephony Gateway Controller IS/GCP IS/GEP IS/GEP AXD AXD Traffic scenario CPB5 CPB6 1slot/board Dual core Dual core One core Two cores running running 2slots/board 2slots/board POTS-POTS / 4.3X call/sec X call/sec 2.3X call/sec 0.4X 2.1X call/sec AGW call/sec OTP R11_3 beta One core used +patches ISUP-ISUP /Inter 13X call/sec 3.6X call/sec 7.7X call/sec 1.55X 7.6X call/sec MGW call/sec OTP R11_3 beta One core used +patches ISUP-ISUP /Intra 5.5X call/sec 26X call/sec 3.17X 14X call/sec MGW call/sec Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 16
  38. 38. Scalability in the small: SMP Case Study: Telephony Gateway Controller IS/GCP IS/GEP IS/GEP AXD AXD Traffic scenario CPB5 CPB6 1slot/board Dual core Dual core One core Two cores running running 2slots/board 2slots/board POTS-POTS / 4.3X call/sec X call/sec 2.3X call/sec 0.4X 2.1X call/sec AGW call/sec OTP R11_3 beta One core used +patches ISUP-ISUP /Inter 13X call/sec 3.6X call/sec 7.7X call/sec 1.55X 7.6X call/sec MGW call/sec OTP R11_3 beta One core used +patches ISUP-ISUP /Intra 5.5X call/sec 26X call/sec 3.17X 14X call/sec MGW call/sec Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 16
  39. 39. Scalability in the small: SMP Speedup on 4 Hyper Threaded Pentium4 5.00 3.96 3.79 3.75 3.63 Speddup 3.11 2.73 2.50 2.05 1.92 1.25 1.00 0 1 2 3 4 5 6 7 8 # Schedulers • Chatty • 1000 processes created • Each process randomly sends req/recieves ack from all other processes Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 17
  40. 40. Scalability in the small: SMP Erlang VM non-SMP VM run queue Scheduler Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 18
  41. 41. Scalability in the small: SMP Erlang VM Current SMP VM run queue OTP R11/R12 Scheduler #1 Scheduler #2 Scheduler #N Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 19
  42. 42. Scalability in the small: SMP Erlang VM New SMP VM OTP R13 Scheduler #1 run queue Released 21th April migration Scheduler #2 run queue logic Scheduler #N run queue Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 20
  43. 43. Scalability in the small: SMP Multiple run queues Speedup: Ca 0.43 * N @ 32 cores Memory allocation locks dominate... Single run queue • Speedup of ”Big Bang” on a Tilera Tile64 chip (R13A) • 1000 processes, all talking to each other Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 21
  44. 44. Scalability in the small: SMP Shift in Bottlenecks • All scalable Erlang systems were stress tested  for CPU usage  for network usage • With SMP hardware we must stress test for memory usage • In the typical SMP system, the bottleneck has shifted from the CPU to the memory Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 22
  45. 45. Scalability in the small: SMP Death by a thousand cuts • Many requests that generate short spikes in memory usage • Limit or serialize those requests • More on this in coming paper from CTO Ulf Wiger loop(State) -> receive {request, typeA, Data} -> Data1 = allocate_lots_of_memory(Data), a_server ! {request, typeA, self()}, receive {answer, … Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 23
  46. 46. Questions ??? Erlang and Scalability Percona Performance Conference © 2009 -2009, Erlang Training and Consulting 24

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