Optimizing the Roc parser/compiler with data-oriented design
The blog post explores optimizing a parser/compiler with data-oriented design (DoD), comparing Array of Structs and Struct of Arrays for improved performance through memory efficiency and cache utilization. Restructuring data in the Roc compiler showcases enhanced efficiency and performance gains.
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This blog post by Tweede Golf discusses the optimization of a parser/compiler using data-oriented design (DoD). DoD focuses on structuring code based on the actual data to improve runtime performance. The post explores the concept of Array of Structs vs. Struct of Arrays, highlighting the advantages of the latter in terms of memory efficiency and cache utilization. By reorganizing data structures in the Roc compiler, the author demonstrates how DoD principles can lead to performance improvements. The post includes examples of transforming data representations to enhance efficiency, such as separating data into parallel arrays and optimizing memory usage. Benchmarks show that the DoD approach results in lower memory consumption and slightly faster runtime compared to traditional approaches. The post emphasizes the importance of aligning code structure with hardware capabilities to achieve optimal performance in data-intensive applications like compilers.
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