Sure thing, but first a quick heads‑up: A* on a tiny device is basically a “tightrope walk” between speed, memory, and correctness. Here’s a bite‑size cheat sheet that might help you shave off a few dozen kilobytes and keep the CPU happy. 1. **Use a small, fixed‑size open list** – a binary heap is nice, but if you know your grid is say 16×16, a simple array that you scan for the minimum is often faster in practice because you avoid the overhead of dynamic memory allocation. 2. **Precompute heuristics** – if the goal never changes, store a small static table of Manhattan or Euclidean distances. Even a 1‑byte per cell can cut the multiplication cost out of the loop. 3. **Avoid floating point** – replace *g* and *h* with integers. If you need a diagonal move cost, use a fixed‑point representation (e.g., 4 bits for fractional part) or just multiply everything by a constant and truncate. 4. **Short‑circuit once you hit the goal** – as soon as you pop the goal node from the open list, stop. No need to keep filling the list. 5. **Use a bitmask for closed nodes** – instead of a bool array, pack 8 nodes per byte. You save memory at the cost of a handful of bit ops, which is usually fine. 6. **Limit the search radius** – if you’re only interested in paths up to, say, 10 steps, give your algorithm a maximum depth. That turns the “infinite” search into a bounded flood fill. 7. **Cache neighbor checks** – if your grid has static obstacles, pre‑store a neighbor offset list per tile type (e.g., wall, corridor). That removes a lot of conditional checks during the loop. 8. **Incremental A*** – if the map changes little over time, keep the previous open/closed lists and only re‑evaluate the affected region instead of recomputing everything from scratch. 9. **Profile on the target hardware** – a micro‑second saved in the loop is meaningful when the CPU is already chewing at the limit. Try piecing these together in a minimal demo and see where the bottlenecks are. If you hit a specific wall, drop the code snippet and we can dig deeper. Good luck, and remember: the goal is to keep the code as small as the device, not the other way around.