The author challenges the RAM myth by discussing how cache optimization can significantly impact data processing speed. They provide an example of a Python sharding algorithm that can be improved by leveraging cache-friendly techniques, such as sorting elements by group to prevent cache misses. Various optimization strategies, including using radix sort and minimizing memory allocations, are explored to enhance performance. Ultimately, the author emphasizes the importance of considering optimization trade-offs, especially for large datasets, and suggests that partitioning data or utilizing external memory algorithms may be necessary for efficient processing. This insightful article offers valuable tips for maximizing performance in data handling, but it may be controversial due to its complex nature and machine-dependency of certain optimizations.
https://purplesyringa.moe/blog/the-ram-myth/