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Graph Algorithms: From Theory to Optimization (Examples in Rust)

  • The article delves into graph algorithms, transitioning from theory to optimization with examples in Rust.
  • The research focuses on developing a 3D engine based on the ECS architecture, encountering challenges in scheduling systems efficiently.
  • Understanding Big O notation is crucial as it describes the algorithm's performance relative to input size.
  • Different representations of graphs like adjacency lists and matrices are discussed for memory efficiency and complexity.
  • The concept of squared graphs (G²) and path lengths of 2 in graphs are explained.
  • Bitwise operations and SIMD are introduced as optimizations for graph calculations, showcasing performance gains.
  • The article explores parallelization in graph algorithms, highlighting the benefits and considerations.
  • Various benchmarks and tests were conducted to compare different implementations, emphasizing the importance of simplicity and efficiency.
  • The article concludes by providing a link to the complete code and resources on GitHub for further exploration.

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