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uma-rfc: update to questions/comments added #6

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6 changes: 3 additions & 3 deletions rfcs/00xx_UMA_Unified_Modular_Accelerator_Interface.md
Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@ The **goal** of UMA is to establish two API layers with a different target group
- Short learning period for hardware/software engineers new to TVM

**Plumbing Layer**:
- Collage-like API + other TVM APIs
- Collage-like API [COLLAGE-RFC](https://github.com/mbs-octoml/mbs-tvm-rfcs/blob/mbs-rfcs-collage/rfcs/xxxx-collage.md) + other TVM APIs
- Powerful API to core-compiler + other TVM features
- Target audience is experienced TVM users/developers
- C++ and Python APIs
Expand Down Expand Up @@ -88,7 +88,7 @@ The figure below described the *UMA Pipeline*. The blocks are described below:
![](uma_pipeline.png)

UMA Pipelining:
* Consists of UMALower and UMACogen, which implement the target hook Relay-to-TIR and TIR-to-Runtime (proposed in [TVM-RFC0010])
* Consists of UMALower and UMACodgen, which implement the target hook Relay-to-TIR and TIR-to-Runtime (proposed in [TVM-RFC0010])
* UMALower
* Input: Partitioned composite functions
* Custom primitives can be registered
Expand All @@ -104,7 +104,7 @@ UMA Pipelining:
* UMACodegen baseclass has to be inherited by accelerator-specific Codegen classes (e.g. Accelerator A Codegen, etc)
* Output: Target .c files

The intention is to use TensorIR with MetaScheduler for optimization and Relax in later versions.
The intention is to use TensorIR with MetaScheduler for optimization and Relax (a possible succesor of Relay [video link](https://www.youtube.com/watch?v=xVbkjJDMexo)) in later versions.


Abbreviations:
Expand Down