MIT OpenCourseWare

MIT 6.172 Performance Engineering of Software Systems, Fall 2018

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

MIT 6.034 Artificial Intelligence, Fall 2010

  1. Introduction and Scope
  2. Reasoning: Goal Trees and Problem Solving
  3. Reasoning: Goal Trees and Rule-Based Expert Systems
  4. Search: Depth-First, Hill Climbing, Beam
  5. Search: Optimal, Branch and Bound, A*
  6. Search: Games, Minimax, and Alpha-Beta
  7. Constraints: Interpreting Line Drawings
  8. Constraints: Search, Domain Reduction
  9. Constraints: Visual Object Recognition
  10. Introduction to Learning, Nearest Neighbors
  11. Learning: Identification Trees, Disorder
  12. Neural Nets / Deep Neural Nets
  13. Learning: Genetic Algorithms
  14. Learning: Sparse Spaces, Phonology
  15. Learning: Near Misses, Felicity Conditions
  16. Learning: Support Vector Machines
  17. Learning: Boosting
  18. Representations: Classes, Trajectories, Transitions
  19. Architectures: GPS, SOAR, Subsumption, Society of Mind
  20. Probabilistic Inference I
  21. Probabilistic Inference II
  22. Model Merging, Cross-Modal Coupling, Course Summary
  • Mega-R1. Rule-Based Systems
  • Mega-R2. Basic Search, Optimal Search
  • Mega-R3. Games, Minimax, Alpha-Beta
  • Mega-R4. Neural Nets
  • Mega-R5. Support Vector Machines
  • Mega-R6. Boosting
  • Mega-R7. Near Misses, Arch Learning

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