5.7. Chapter Summary

  • Intermediate Representation (IR) serves as one of the fundamental data structures of a compiler. It represents the transition from the source language to the target language during the process of program compilation.

  • Classical compilers categorize IRs into three types based on their structure: linear IR, graphical IR, and hybrid IR.

  • The demands imposed by machine learning frameworks necessitate new forms of IRs, as classical IRs fail to fully satisfy these requirements. Therefore, innovative IRs that are more compatible with these frameworks must be developed based on classical IRs.

  • The central principle in automatic differentiation is the decomposition of a program’s arithmetic operations into a finite set of basic operations. Knowing the derivative evaluation rules for all these operations allows for the calculation of the derivative for each basic operation. Subsequently, these results are aggregated using the chain rule to obtain the derivative result for the entire program.

  • Automatic differentiation operates in two modes—forward-mode and reverse-mode—based on the sequence adopted by the chain rule for combining derivatives.

  • Forward-mode automatic differentiation is applied when evaluating the derivative of a network where the input dimension is smaller than the output dimension. In contrast, reverse-mode automatic differentiation is employed when the output dimension of a network is smaller than the input dimension.

  • Implementation methods for automatic differentiation encompass elemental libraries, operator overloading, and source transformation.

  • Type systems, which are utilized to define various types, detail the operations of each type and outline the interactions among types. Comprising a set of types and the type-based rules that delineate program behavior, type systems are extensively used in compilers, interpreters, and static checking tools.

  • Static analysis involves the inspection and verification of code through lexical analysis, syntactic analysis, control flow analysis, and data flow analysis, all of which are conducted without executing the programs.

  • The objective of compilation optimization is to boost the efficiency of the IRs generated during the compilation process. Notably, compilation optimization conducted at the frontend is hardware-agnostic.