Hi @aca88
thanks for your interest! For the evaluated models, we just used a single schedule as given by TVM: https://github.com/tum-ei-eda/tvm/blob/tumeda_memplan/python/tvm/relay/memplan.py#L187 You are right that for more complex graphs, we would have to evaluate more schedules to find the optimal solution. However, getting all topological sorts is a bit of a lazy overkill. I have not looked into this in detail yet, but some thoughts: - Only need to evaluate parallel paths independently - On nested parallel paths, work inside-out - The optimal order within parallel paths is dependent on the maximum and minimum usage of the individual nodes. I'm sure there is a good algorithm for this, better than the brute-force approach --- [Visit Topic](https://discuss.tvm.apache.org/t/discussion-alignment-memory-planning/9730/8) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/fe49429d1a18d02ea36f9172906f7802fd41a0bd3e89dc8d9ddc748b13dd48fd).
