Project 5: Entity Component System (ECS) with SOA

A data-oriented Entity Component System using Odin’s #soa attribute, demonstrating cache-friendly game architecture with systems that process components efficiently.

Quick Reference

Attribute Value
Primary Language Odin
Alternative Languages C++, Rust
Difficulty Level 3: Advanced
Time Estimate 2 weeks
Knowledge Area Game Architecture / Data-Oriented Design
Tooling Custom implementation with #soa
Prerequisites Project 4 (Game with Raylib), understanding of data locality

What You Will Build

A data-oriented Entity Component System using Odin’s #soa attribute, demonstrating cache-friendly game architecture with systems that process components efficiently.

Why It Matters

This project builds core skills that appear repeatedly in real-world systems and tooling.

Core Challenges

  • Understanding AoS vs SoA trade-offs → maps to cache-friendly design
  • Using #soa with slices and dynamic arrays → maps to Odin’s SOA support
  • Designing component queries → maps to bit_sets for component masks
  • Efficient iteration patterns → maps to data-oriented thinking

Key Concepts

  • SOA in Odin: Odin Overview - SOA
  • Data-Oriented Design: “Data-Oriented Design” by Richard Fabian
  • ECS Architecture: “Game Programming Patterns” Ch. 14
  • Cache Performance: “Computer Systems: A Programmer’s Perspective” Ch. 6

Real-World Outcome

$ odin run ecs_demo

ECS Demo - 100,000 Entities
---------------------------

Memory Layout Comparison:
  AoS (Array of Structs): Components interleaved
  SoA (Struct of Arrays): Components contiguous

  Entity struct size: 64 bytes
  AoS total: 6.4 MB
  SoA total: 6.4 MB (same, but layout differs)

System: MovementSystem (Position + Velocity)
  Entities with components: 100,000
  AoS iteration: 12.3 ms
  SoA iteration: 2.1 ms  ← 5.8x faster!

System: RenderSystem (Position + Sprite)
  Entities with components: 85,000
  AoS iteration: 15.7 ms
  SoA iteration: 3.2 ms  ← 4.9x faster!

System: PhysicsSystem (Position + Velocity + Collider)
  Entities with components: 50,000
  AoS iteration: 8.4 ms
  SoA iteration: 1.8 ms  ← 4.7x faster!

Why SoA is faster:
  - CPU loads entire cache lines (64 bytes)
  - SoA: 16 positions loaded per cache line
  - AoS: Only 1 entity per cache line (other data wasted)

Running visual demo with 10,000 entities...
[Window opens showing thousands of moving/colliding entities]

Implementation Guide

  1. Reproduce the simplest happy-path scenario.
  2. Build the smallest working version of the core feature.
  3. Add input validation and error handling.
  4. Add instrumentation/logging to confirm behavior.
  5. Refactor into clean modules with tests.

Milestones

  • Milestone 1: Minimal working program that runs end-to-end.
  • Milestone 2: Correct outputs for typical inputs.
  • Milestone 3: Robust handling of edge cases.
  • Milestone 4: Clean structure and documented usage.

Validation Checklist

  • Output matches the real-world outcome example
  • Handles invalid inputs safely
  • Provides clear errors and exit codes
  • Repeatable results across runs

References

  • Main guide: LEARN_ODIN_PROGRAMMING_LANGUAGE.md
  • “Data-Oriented Design” by Richard Fabian