Performance Engineering of Software Systems (MIT 6.172) - Video lectures 2018
Charles Leiserson and Julian Shun

@article{,
title= {Performance Engineering of Software Systems (MIT 6.172) - Video lectures 2018},
journal= {},
author= {Charles Leiserson and Julian Shun},
year= {2018},
url= {https://ocw.mit.edu/6-172F18},
abstract= {Modern computing platforms provide unprecedented amounts of raw computational power. But with great power comes great complexity, to the point that making useful computations exploit even a fraction of the computing platform's potential becomes a substantial challenge. Indeed, obtaining good performance requires a comprehensive understanding of all layers of the underlying platform, deep insight into the computation at hand, and the ingenuity and creativity required to obtain an effective mapping of the computation onto the machine. The reward for mastering these sophisticated and challenging topics is the ability to make computations that can process large amounts of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice.

This is an 18-unit class that provides a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems.

**Main course URL:** https://ocw.mit.edu/6-172F18

**Contents:**

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

---

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keywords= {computer science,computer engineering,high-performance computing},
terms= {https://ocw.mit.edu/terms},
license= {https://creativecommons.org/licenses/by-nc-sa/4.0/},
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}