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Performance Engineering of Software Systems

MIT 6.172 · Software · Spring 2028 · Planned

Lectures

  1. Lecture 1: Introduction and Matrix Multiplication (1:00:20)
  2. Lecture 2: Bentley Rules for Optimizing Work (1:20:10)
  3. Lecture 3: Bit Hacks (1:18:54)
  4. Lecture 4: Assembly Language and Computer Architecture (1:17:34)
  5. Lecture 5: C to Assembly (1:21:30)
  6. Lecture 6: Multicore Programming (1:16:46)
  7. Lecture 7: Races and Parallelism (1:14:39)
  8. Lecture 8: Analysis of Multithreaded Algorithms (1:17:34)
  9. 9. What Compilers Can and Cannot Do (1:18:46)
  10. 10. Measurement and Timing (1:21:28)
  11. 11. Storage Allocation (1:05:25)
  12. 12. Parallel Storage Allocation (1:17:21)
  13. 13. The Cilk Runtime System (1:21:46)
  14. 14. Caching and Cache-Efficient Algorithms (1:18:23)
  15. 15. Cache-Oblivious Algorithms (1:21:47)
  16. 16. Nondeterministic Parallel Programming (1:22:12)
  17. Lecture 17: Synchronization Without Locks (1:20:10)
  18. Lecture 18: Domain-Specific Languages and Autotuning (1:11:22)
  19. Lecture 19: Leiserchess Codewalk (1:12:42)
  20. Lecture 20: Speculative Parallelism and Leiserchess (1:23:03)
  21. Lecture 21: Tuning a TSP Algorithm (1:20:52)
  22. Lecture 22: Graph Optimization (1:18:39)
  23. Lecture 23: High Performance in Dynamic Languages (1:25:44)

Notes

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