Update ToC

Author: mikebo93

.DS_Store

@@ -24,3 +24,15 @@ This chapter aims to achieve the following learning objectives:
 
 -   Understand the architecture and functionalities of operator
     compilers.
+
+```toc
+:maxdepth: 2
+
+Overview
+Graph_Optimization
+Operator_Selection
+Memory_Allocation
+Operator_Compiler
+Chapter_Summary
+Further_Reading
+```

chapter_compiler_backend/Index.md

@@ -0,0 +1,38 @@
+# AI Compiler Backend
+
+In this chapter, we will explore the design of the AI compiler backend.
+The objective of an AI compiler backend is to enhance the efficiency of
+AI program execution by optimizing the Intermediate Representation (IR)
+generated by the compiler frontend. This optimization enables the full
+utilization of hardware capabilities. The backend achieves this goal by
+applying optimizations to IR code based on hardware capabilities.
+Furthermore, it selects suitable operators based on the capabilities of
+target hardware to execute computations efficiently, while also
+allocating memory to optimize data reuse and locality. Additionally, the
+backend often incorporates an operator compiler, which optimizes the
+execution strategy for code statements associated with operators.
+
+This chapter aims to achieve the following learning objectives:
+
+-   Understand the role and architecture of an AI compiler backend.
+
+-   Understand typical methods for optimizing computational graphs.
+
+-   Understand typical methods for selecting operators.
+
+-   Understand typical methods for memory allocation.
+
+-   Understand the architecture and functionalities of operator
+    compilers.
+
+```toc
+:maxdepth: 2
+
+Overview
+Graph_Optimization
+Operator_Selection
+Memory_Allocation
+Operator_Compiler
+Chapter_Summary
+Further_Reading
+```