Hey @srush,
Thanks for asking! We are actively developing a more straightforward scheduling language and a new IR called TensorIR: * imperative scheduling: each schedule primitive is like applying a compiler pass that transforms the TensorIR to a new TensorIR - you can see and debug the scheduling result immediately after each step. * python-first: each step results in a new TensorIR, which can be printed into python syntax, as well as be parsed back to schedule status. The TensorIR syntax is designed to be completely human readable and manipulatable. * Tensorization: we extend our tensorization capability and allows possibility for competitive GEMM perf. * In your particular case, we provide a primitive called `reverse_compute_at`, which computes the consumer under the specific loop of the producer. The shape of the computed region is handled automatically in our schedule - so you don’t have to repetitive splitting RFC: https://discuss.tvm.apache.org/t/rfc-tensorir-a-schedulable-ir-for-tvm/7872. We are actively preparing upstreaming our codebase, and will closely update with the community with our latest status :slight_smile: --- [Visit Topic](https://discuss.tvm.apache.org/t/thoughts-on-a-simpler-scheduling-language/9110/2) 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/b94b432f13100b4bf0ac835bbb55485966429865094fe7caac8a85f093bb16ad).
