Performance Engineering of Software Systems (Fall 2018)

Performance Engineering of Software Systems (Fall 2018)

Prof. Charles Leiserson and Prof. Julian Shun via MIT OpenCourseWare Direct link

14. Caching and Cache-Efficient Algorithms

14 of 23

14 of 23

14. Caching and Cache-Efficient Algorithms

Class Central Classrooms beta

YouTube playlists curated by Class Central.

Classroom Contents

Performance Engineering of Software Systems (Fall 2018)

Automatically move to the next video in the Classroom when playback concludes

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

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.