1. Introduction and Matrix Multiplication
1:00:202. Bentley Rules for Optimizing Work
1:20:103. Bit Hacks
1:18:544. Assembly Language & Computer Architecture
1:17:345. C to Assembly
1:21:306. Multicore Programming
1:16:467. Races and Parallelism
1:14:398. Analysis of Multithreaded Algorithms
1:17:34Lecture 9: What Compilers Can and Cannot Do (6.172)
1:18:46Lecture 10: Measurement and Timing (6.172)
1:21:28Lecture 11: Storage Allocation (6.172)
1:05:26Lecture 12: Parallel Storage Allocation (6.172)
1:17:21Lecture 13: The Cilk Runtime System (6.172)
1:21:47Lecture 14: Caching and Cache-Efficient Algorithms (6.172)
1:18:23Lecture 15: Cache-Oblivious Algorithms (6.172)
1:21:47Lecture 16: Nondeterministic Parallel Programming (6.172)
1:22:12Lecture 17: Synchronization Without Locks (6.172)
1:20:10Lecture 18: Domain Specific Languages and Autotuning (6.172)
1:11:22Lecture 20: Speculative Parallelism & Leiserchess (6.172)
1:23:03Lecture 21: Tuning a TSP Algorithm (6.172)
1:20:53Lecture 22: Graph Optimization (6.172)
1:18:407. Races and Parallelism
Professors of Electrical Engineering and Computer Science
This lecture explores the fundamental concepts of races and parallelism in concurrent systems, detailing how cilkscale can be used for determinacy race detection and discussing various types of schedulers for parallel execution.
MIT 6.172 Performance Engineering of Software Systems, Fall 2018
Instructor: Julian Shun
View the complete course: https://ocw.mit.edu/6-172F18
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63VIBQVWguXxZZi0566y7Wf
Seminar notes & discussion
No public seminar notes on this lecture yet.