Algorithms for Game Development (Autumn 2022)

Abstract

Students attending this course will study some of the core algorithms and systems related to game development.

Description

This course will approach some of the algorithms and ideas that are at the core of the development of modern game engines and expand on technical subjects that were seen in the course "Game Programming".

The student will learn the inner workings of game engines both from a technical and algorithmic perspective, touching upon topics such as:

• Entity-component systems
• Game development tools
• Debugging and profiling
• Telemetry
• Hardware acceleration and SIMD
• Data-oriented design
• Building and deployment

Formal prerequisites

The essential skills and requirements are:

• Good programming skill, since the course will propose programming exercises and will require a final project.
• Knowledge of basic data structures, e.g. linked lists and dictionaries.
• Foundational understanding of discrete mathematics and linear algebra.

Optimally the student has completed the course "Game Programming".

Intended learning outcomes

After the course, the student should be able to:

• Use profiling tools to measure code performance
• Implement systems covered during the course in the context of a game engine
• Analyze, implement and explain a topic of their choice. The topic must be related to the core content of the course
• Evaluate game engine technologies and critically assess their application in different development contexts
• Classify and compare different software architectures and relate them to their appropriate application

Learning activities

14 weeks of teaching consisting of lectures, exercises and supervision.

Students are responsible for attending weekly lectures and then working in their groups independently, yet supervised, on their course project.

Mandatory activities

None

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

Chapters from different books as well as research papers will compose the readings.

Student Activity Budget

Estimated distribution of learning activities for the typical student

• Preparation for lectures and exercises: 25%
• Lectures: 25%
• Exercises: 10%
• Project work, supervision included: 20%
• Exam with preparation: 20%

Ordinary exam

Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.

reexam

Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D22: Submission with following oral exam supplemented by the submission.

Time and date