@hht -- thank you very much.
So is this mean, we can not enforce parallelism to GraphRuntime? If I understand correctly, it looks like GraphRuntime does not run add1 and add2 in parallel? Basically, I am wondering if there is a mechanism to enforce parallelism to GraphRuntime from the higher level passes from Relay/TVM? For example embedding scheduling (parallelism information) into the graph json file, and enforce that schedule into GraphRuntime? [quote="hht, post:2, topic:6572"] Each subgraph has been made a fused function. So I guess the former pass bind the thread and it is not suggested to explore it in graph runtime. The graph runtime use an static memory allocation strategy and will be replaced by Relay VM. [/quote] --- [Visit Topic](https://discuss.tvm.ai/t/execution-order-of-operators-at-runtime-in-tvm/6572/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai/email/unsubscribe/2062c095b9c4ea2277072c9ca194d73cc88d716aaaa05ab307c477845be6af32).
