1. Evolving neural brains in
JavaScript, multi-threaded!
@Lukasz-pluszczewski

2. github.com/Lukasz-pluszczewski

3. multithreading in Node.js
why?
simulation — how? did it work?
agenda:

4. why

5. why

6. why

8. directed by "natural" selection only
behaviours not scripted
random changes
goals:

9. neural networks

10. neural networks

11. 10
10
5
neural networks

12. 10 x 0
10 x -0.1
5 x 0.3
neural networks

13. 10 x 0
10 x -0.1
5 x 0.3
Tanh
neural networks

14. neural networks
10 x 0
10 x -0.1
5 x 0.3
0.46
Tanh

15. neural networks

16. neural networks

17. simulation

18. simulation

19. simulation

20. simulation

21. simulation

22. simulation

23. simulation

24. simulation

25. simulation

26. simulation

27. simulation

28. simulation

29. simulation

30. simulation

31. simulation

32. simulation

33. simulation

34. simulation

35. simulation

36. simulation

37. simulation

38. simulation 1

39. simulation 1

40. simulation 1

41. simulation 2

42. multithreading
in Node.js

43. Multicore!!!111!
POWERFULL
POWERFULL

44. communication through IPC
spawns separate Node.js process
heavy
child_process:

45. light weight
runs new event loop in a separate thread
the same process
worker_threads
memory block can be transfered
(ArrayBuffer)
and even shared (SharedArrayBuffer)

46. worker_threads

47. threads.js

48. threads.js

49. threads.js

50. threads.js

51. threads.js

52. threads.js

53. threads.js

54. WAT?
generation: 138ms
calculating inputs: 2µs
synchronous
generation: 543ms
calculating inputs: 22µs
async
async with inputs calculated in threads
generation: 1s
calculating inputs: 713µs

55. WAT?
generation: 138ms
calculating inputs: 2µs
synchronous
generation: 162ms
calculating inputs: 3.1µs
async
async with inputs calculated in threads
generation: 291ms
calculating inputs: 15µs

56. conclusions & what next

57. conclusions & what next
generation: 138ms
calculating inputs: 2µs
synchronous
generation: 162ms
calculating inputs: 3.1µs
async
async with inputs calculated in threads
generation: 291ms
calculating inputs: 15µs

58. conclusions & what next
hard to create right conditions
hyperparameter optimization
neural networks are hard
many variables to optimize
right amount for work
multithreading is not always better

59. useful links
https://github.com/Lukasz-pluszczewski/creatures
https://www.oreilly.com/library/view/learning-
tensorflowjs/9781492090786/
https://towardsdatascience.com/how-to-choose-the-right-
activation-function-for-neural-networks-3941ff0e6f9c
resources:

60. thank you