1. Open your favorite sampling profiler (vtune, zoom, instruments, whatever) 2. Set it up to sample every N cache misses. Good choices of N absent extra inform

1. Open your favorite sampling profiler (vtune, zoom, instruments, whatever) 2. Set it up to sample every N cache misses. Good choices of N absent extra information are usually prime (why? to avoid artifacts where cache misses are divided evenly among M locations, with M|N) numbers between ~1000 and ~1000000. 3. Exercise your program under typical workload. If the resulting data is too coarse-grained, decrease N. If your program is running too slowly because of sampling overhead, increase N. 4. You now have a detailed accounting of what call stacks and instructions triggered cache misses. Starting with the worst offenders, re-arrange your algorithms to maximize the amount of data reuse. This isn't trivial, but I’d say it’s a very long way from primitive.