Matrix Multiply: A Case Study 
Matrix Multiply: A Case Study
by MIT
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Date Added: July 16, 2017

Lecture Description

Lecture 1: Matrix Multiply: A Case Study
Instructor: Charles Leiserson, Saman Amarasinghe
View the complete course: ocw.mit.edu/6-172F10

License: Creative Commons BY-NC-SA
More information at ocw.mit.edu/terms
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Course Description

This class is 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, cache and memory hierarchy optimization, parallel programming, and building scalable distributed systems.

Modern computing platforms provide unprecedented amounts of raw computational power. But significant complexity comes along with this power, to the point that making useful computations exploit even a fraction of the potential of the computing platform is 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 amount of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice.

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