The Speed Game: Automated Trading Systems in C++

on YouTube ↗01h 05m

" summary

Shows concrete claims, code and measurements: lists 1–10 µs typical C++ software path versus ~100 ns hardware/FPGA; explains BIOS/OS/network tuning, user‑space drivers, cache‑warming, memory pools and a variadic compile‑time logging/GitHub implementation; demonstrates a measurement rig with a fake exchange and packet‑timestamp measurement that matches market events to orders; reports real benchmarks (sort, GCC string changes) and failures like IPC cache thrashing so the optimizations are practical and validated rather than rhetorical.

AI-written summary · about

" chapters (48)

1. 0:00Introduction
2. 0:34Overview
3. 1:32About Carl
4. 2:33General Performance
5. 5:43Speed doesnt matter
6. 5:59How fast is actually fast
7. 10:05Low latency code
8. 13:04Fast path
9. 13:19High frequency trading
10. 14:13Buy good servers
11. 14:27Tuning
12. 15:06Trading Algorithms
13. 16:43Changing Servers
14. 19:36Heuristics
15. 24:07System calls
16. 24:43Buying more servers
17. 25:22General considerations
18. 25:57Standard vs CQ sort
19. 26:44Google Benchmark
20. 27:05Consecration
21. 28:20Octave Area
22. 29:24Memory Management
23. 30:19Move
24. 30:38Log Macro
25. 32:11Copy Arc
26. 33:19Smart Compilers
27. 34:36Shortcircuiting
28. 35:27Compiler assumptions
29. 35:58Overflow check
30. 37:04Floats
31. 37:37Hardware Branch Predictor
32. 39:14Error Control
33. 40:27Exceptions
34. 41:27Hot Path
35. 41:55clang
36. 44:25lambda functions
37. 46:14GCC 5 is faster
38. 47:04Boom Boom Link
39. 48:33User Space
40. 49:40Concurrency
41. 49:54Multithreading
42. 50:11Measurement
43. 50:37What do we do
44. 52:19Observer effect
45. 53:30Cache warming
46. 54:44Inplace function
47. 55:53Summary
48. 57:27Questions

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