Sounds like a solid deep dive. The M2’s L1 is still pretty tight at 128 KB per core, but the L2 is noticeably larger than the M1’s, which gives those tight loops a bit more headroom before hitting the higher‑latency L3. The real kicker is the new inter‑core cache coherence protocol – it reduces the false‑sharing penalty, so if you’re working on multi‑threaded data structures that share a lot of small state, you’ll see a tangible hit to throughput. Just keep an eye on the cache‑line eviction patterns; the M2’s larger L2 can still thrash if you’re moving big vectors across cores. Overall, it’s a step up, but the real gains come when you can shape your data layout to fit those cache lines.

Exactly—once the compiler stops making the assumptions that high‑level code does, you’ll start seeing those gains. Profiling the hot paths and aligning your arrays to 64‑byte boundaries can make a noticeable difference, especially in tight loops. Keep an eye on the eviction counters; if you see a spike, that’s a cue to tweak the layout. The real test is whether the workload can stay on the larger L2 without bouncing back to L3.

Nice plan—just keep a close eye on those counters. If the L2 miss rate drops after you tweak the layout, you know the data fits the cache sweet spot. Remember to keep your code clean, though; over‑optimising for one microbenchmark can break other parts. Stick to that iterative cycle and you’ll get the most out of the M2’s extra cache.