Code Transformation and Optimization

In modern computer science and engineering, code transformation techniques are critical to achieve the combined goals of combining programmer productivity and program execution efficiency in terms of time and energy. Yet, it is a skill mastered by few – there are less than 1.5 compiler construction expert for every 1000 software engineers, but almost 2 jobs in compilers for every 100 in software engineering!

The course is designed to provide an overview of code transformation, analysis and optimization techniques needed to effectively produce optimized code.

To compiler and EDA tool engineers, the course provides the basic tools to design and implement compilers and other code transformation and analysis tools, as well as an introduction to the most popular modern compiler framework, LLVM.

To software engineers, the course provides a grounding in system software design and development, as well as insights on the benefits and limitations of automation in software engineering. Moreover, as a compiler is a paramount of complex software systems, it provides a hands-on introduction to the design and implementation process for such systems. Finally, many advanced software engineering techniques such as program slicing are implemented on top of algorithms used in compiler construction.

To computer architects and embedded software engineers, the course provides crucial insights on the power and limits of compiler optimization, as well as to the need any processor architecture has of appropriate compilers.

To all computer science students, the course provides a “behind the scenes” view of the operation of software, and its automated manipulation – understanding compilers means being able to write better, more efficient code.

Introduction to Compiler Construction

• Why compiling? Compilers vs interpreters

• When to compile? JIT, AOT and static compilers

• What to compile? Compilation units

• Where to compile? Cross-compilation and split compilation

• Overview of a compiler framework

  • Lexical analysis & parsing (review)

  • Statement and Data Structure Lowering

  • Optimization: machine independent and machine-dependent

  • Code Generation

Reading: Compiler Construction

Intermediate Representations

• The Abstract Syntax Tree

• Basic Blocks and branches

• The Control Flow Graph

• The Static Single Assignment Form

Reading: Program Dependence Graph

Reading: The SUIF Compiler Framework

Semantic Analysis & Type Checking

• Symbol Tables

• Type Checking

Runtime Organization

• Data Memory layout

• Activation Records

• Dynamic Memory allocation

Reading: Garbage Collection

Code Generation

• Code generation techniques: CISC and RISC processors

• Low-level optimization techniques

Reading: Low-level Optimization

Dataflow Optimization

• Principles and Fixed Point Computation

• Applications

  • Reaching Definitions

  • Liveness Analysis

  • Constant Propagation

Reading: Dataflow Optimizations

Register Allocation

• When to allocate registers

• Graph Coloring

• Linear scanning

Reading: Linear Scan Register Allocation

Parallelization and other optimization techniques

• Instruction Scheduling

• Loop Optimization (Software Pipelining, Loop Unrolling)

• Limits to optimization: the aliasing problem

Reading: Program Optimization  

Reading: Alias Analysis

Reading: Cache Optimization

Advanced Topics

Advanced Optimization Techniques: Polyhedral Transformations

The LLVM Compiler Framework

Laboratory

• The sessions will be organized as follows:

  • Recursive descent language parsing

  • Transforming the Abstract Syntax Tree into a Control Flow Graph

  • Design and implementation of the symbol table

  • Function call translation

  • Liveness analysis

  • Register allocation (linear scan)

  • ARM code generation (table-based)

Readings

The papers presented in this bibliography are mostly for those who wish to get deeper insight on a specific topic.

Compiler Construction

LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation, by C. Lattner and V. Adve.

Intermediate Representations

The Program Dependence Graph and Its Use in Optimization, by J. Ferrante et al.

The Basic SUIF Programming Guide, by G. Aigner et al.

Alias Analyis

Interprocedural pointer alias analysis, by M. Hind et. al.

Register Allocation

Linear Scan Register Allocation, by M. Poletto and V. Sarkar.

Optimization

Compiler Transformations for High-Performance Computing, by D. Bacon et al.

Cache Optimization

A Retrospective: A Data Locality Optimizing Algorithm, by M. S. Lam.

Garbage Collection

Uniprocessor Garbage Collection Techniques: a complete survey of Garbage Collection by P. Wilson.

The course is mostly self-contained. Knowledge of imperative and object-oriented programming (as provided in the Laurea in Ingegneria Informatica) is necessary, and an understanding of parsing techniques is useful (however, the necessary concepts of recursive descent parsing are introduced in the first lecture and observed in practice in the first laboratory). Also, a basic understanding of computational complexity (once more, as provided in Laurea in Ingegneria Informatica) is useful.

The project/laboratory work can be conducted in Python or C++.

Assessment

Evaluation is performed through a combination of oral exam and project work.

The similar, but earlier, book "Modern compiler implementation in C" by Appel is available online for free download.

We use only Chapter 11