[RFC] TensorIR: A schedulable IR for TVM

[aca88]

Hi,

Even though I don’t think I understood everything, I like the idea of solving some of the limitations of te.compute. Since the te.compute is in a central part of the TVM stack changing it requires a lot of work and understanding. So thank you all for continuing such development.

Q1: I was wondering how this fits in the Relay ->Topi->TE->TIR flow. In a more specific case take FuseOps. AFAIK the FuseOps pass creates the multi-stage operator based on the te.computes. Since you mentioned that there would be no notion of a stage in the new TensorIR, how would FuseOps work? and more generally how TVM’s philosophy of “defining a compute rule and a separate schedule” be changed?

@Hzfengsy

TE has limited expressiveness since each stage is defined by Stage = te.compute(lambda expr) , while TensorIR is a full c+±like IR. We can write any program with TensorIR as you want. Although not all programs can be scheduled, there are still more workloads that can be optimized by TensorIR.

Q2: What exactly do you mean by “not all program can be scheduled”? maybe an example?

Q3: You mentioned “new scheduling primitives”, could you maybe give a list?

EDIT: Q4: Expected timeline of the steps?