CSCI 358
Applied Algorithms Spring 2020
Division III Quantative/Formal Reasoning
This is not the current course catalog

Class Details

This course is about bridging the gap between theoretical running time and writing fast code in practice. The course is divided into two basic topics. The first is algorithmic: we will discuss some of the most useful tools in a coder’s toolkit. This includes topics like randomization (hashing, filters, approximate counters), linear and convex programming, similarity search, and cache-efficient algorithms. Our goal is to talk about why these efficient algorithms make seemingly difficult problems solvable in practice. The second topic is applications: we will discuss how to implement algorithms in an efficient way that takes advantage of modern hardware. Specific topics covered will include blocking, loop unrolling, pipelining, as well as strategies for performance analysis. Projects and assessments will include both basic theoretical aspects (understanding why the algorithms we discuss actually work), and practical aspects (implementing the algorithms we discuss to solve important problems, and optimizing the code so it runs as quickly as possible).
The Class: Format: lecture
Limit: 24
Expected: 24
Class#: 3954
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: a course-long project and written final exam, in addition to shorter programming assignments and problem sets
Prerequisites: CSCI 256 or permission of instructor
Enrollment Preferences: current or expected Computer Science majors
Distributions: Division III Quantative/Formal Reasoning
QFR Notes: The course will consist of programming assignments and problem sets in which quantitative/formal reasoning skills are practiced and evaluated.

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