March 3, 2026
Cache me outside
Time, Space, and Life as We Know It (2017)
Coders go to war over recursion as ‘save it once’ trick promises faster pics—and universe sims
TLDR: The piece shows how splitting images into chunks and saving repeated results can speed things up, even hinting at universe-like simulations. Comments turned into a slugfest between fans of caching and skeptics of recursion, with memes flying over whether this is smart optimization or needless complexity.
Raganwald drops a brainy piece on quadtrees (a way to split pictures into four chunks over and over) and how remembering past work—aka memoization—can make rotations and mash-ups way faster. He even teases simulating the universe. The community? Absolute fireworks. One camp chants “recursion is beautiful,” the other waves the infamous “Recursion is a pile of dog faeces” meme like a battle flag.
Optimization fans cheer the simple rule: if you’ve done it once, don’t do it again. They explain it like saving answers in a notebook so you don’t redo homework. Purists clap back: you’re just hiding slowness behind a cache and calling it genius. The “premature optimization” brigade storms in, demanding boring arrays and fewer brain puzzles.
Jokes landed hard. “Cache me outside” became the thread’s rally cry. Someone declared, “I for one welcome our quadtree overlords,” while another posted pixel art claiming their fridge now “simulates the cosmos.” Practical folks kept it grounded: blank regions mean big gains, and remembering identical chunks can turn heavy work into quick lookups. Skeptics weren’t moved, calling it academic cosplay. Whether you love tidy duplicates (canonicalization) or hate fancy math, this Raganwald piece lit up the internet with spicy, hilarious takes.
Key Points
- •Naïve array algorithms are O(n); naïve quadtree algorithms are O(n log n).
- •Coloured quadtrees can process uniform regions in one step, improving performance and sometimes beating naïve arrays when many regions are blank.
- •Identical sub-quadrants can be memoized so results are reused instead of recomputed during operations like rotation.
- •A worked example shows repeated sub-quadrants enabling up to 25% savings in a quadrant and further savings across other quadrants.
- •The article sets up implementing a memoized rotation function to exploit repeated structures in quadtrees.