[GitHub] [tvm-rfcs] junrushao1994 commented on a change in pull request #22: [RFC][TIR] TIR Non-scalar Constants

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junrushao1994 commented on a change in pull request #22:
URL: https://github.com/apache/tvm-rfcs/pull/22#discussion_r704746507



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File path: rfcs/0022-tir-non-scalar-constants.md
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+- Feature Name: tir_non_scalar_constants
+- Start Date: 2021-06-01
+- RFC PR: https://github.com/apache/tvm-rfcs/pull/22
+- GitHub Issue: TBD
+
+# 1. Summary
+
+This RFC proposes how non-scalar constants could be represented in TIR and used by passes in the lowering process.
+
+# 2. Motivation 
+
+Currently, the non-scalar constants could be represented in Relay (relay.Constant) to be used by relay passes but not in TIR. Therefore, when performing lowering using TIR passes, we have to maintain a side-channel of tir::Var to constant non-scalar data mapping to perform transformations that could use the knowledge where some of the data are constants.
+
+Few example scenarios as further motivation :
+
+## Weight compression
+
+When lowering for accelerators (E.g. : [Arm(R) Ethos(TM)-U NPU](https://github.com/apache/tvm-rfcs/pull/11)), certain operations will need to get tiled to co-optimize performance and memory utilization. Such tiling patterns create slices of weights that need compressing that will end up with varying sizes. Therefore, the knowledge of some tir::Vars refer to constants are critical in the level of TIR to perform this.
+
+## Memory Planning
+
+The TIR program has the ability to express both inter and intra operator memory requirement, post-scheduling as explained further by [Unified Static Memory Planning RFC](https://github.com/apache/tvm-rfcs/pull/9). It would be better if the constants could be embedded to the TIR PrimFunc. Moreover, this allows various [target-dependent lowerings](https://github.com/apache/tvm-rfcs/pull/10), to produce TIR PrimFuncs with constants in it.
+
+## Winograd Constants
+
+The Winograd transformation (used for fast GEMMs) involves multiplication by a hard-coded constant tensor. This is currently accomplished in TE using a complicated TE compute expression with many nested selects. Being able to directly express a constant tensor here would significantly simplify this code.

Review comment:
       Thanks @manupa-arm! This is the particular case in my mind that we didn't do well with TE, where we use a lot of if-then-elses to represent a winograd array :-) Therefore, if I understand correctly, this is not going to be addressed within the scope of this RFC. Is that accurate? Thanks in advance!




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