ashutosh-arm commented on a change in pull request #15:
URL: https://github.com/apache/tvm-rfcs/pull/15#discussion_r686028681



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File path: rfcs/0015_Arm_CMSIS-NN_Integration.md
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+- Feature Name: [RFC] Use CMSIS-NN with TVM
+- Start Date: July 2021
+- RFC PR: https://github.com/apache/tvm-rfcs/pull/15
+- GitHub Issue: https://github.com/apache/tvm/issues/8646
+
+# Acronyms
+CMSIS: Common Microcontroller Software Interface Standard
+ACL: The Compute Library for the ArmĀ® Architecture
+MLF: Model Library Format
+
+# Summary
+
+This RFC introduces plan of integration of CMSIS-NN library into TVM. It 
consists of efficient kernels targeted for Arm's Cortex-M architecture.
+
+Please refer to the following pages for more details on CMSIS-NN.
+https://arm-software.github.io/CMSIS_5/NN/html/index.html
+https://github.com/ARM-software/CMSIS_5/tree/develop/CMSIS/NN
+
+First PR in the series of PRs to fulfill this integration would be graph 
partitioner for softmax int8. Detailed plan can found below in this RFC.
+
+
+# Motivation
+
+CMSIS-NN library consists of hand-tuned kernels that are suitable for Cortex-M 
and are compliant with the quantization scheme used in Tensorflow Lite. They 
have been optimized for better performance and small memory footprint which is 
required on these embedded devices and it would make sense for TVM to reuse 
these while generating code for Cortex-M. They have been integrated with the 
TensorFlow Lite Micro project.
+
+
+# Guide-level explanation
+
+TVM's external code generation infrastructure allows for the automatic 
partitioning and code generation using the external compiler. Partitioned 
subgraphs containing operator(s) targeted for Cortex-M can then be translated 
into the CMSIS-NN C APIs which eventually become part of MLF. For this 
integration, we are heavily dependent on the TVM's infrastructure for external 
code generation.

Review comment:
       Dropped the word automatic.




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