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CS153: Compilers

Greg Morrisett Fall 2013. CS153: Compilers. What is the course about?. Compilers. (duh) Translating one programming language into another. Also interpreters. Translating and running a language from within another language. Basic Architecture. Source Code. Parsing. Elaboration.

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CS153: Compilers

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  1. Greg Morrisett Fall 2013 CS153: Compilers

  2. What is the course about? • Compilers. • (duh) • Translating one programming language into another. • Also interpreters. • Translating and running a language from within another language.

  3. Basic Architecture Source Code Parsing Elaboration Lowering Code Generation Optimization Target Code

  4. Front End • Lexing & Parsing • From strings to data structures • Usually split into two phases: Strings/Files Tokens Abstract Syntax Trees Lexing Parsing

  5. Parsing Tools • Parsing is something that happens in essentially all applications. • E.g., Google search bar, calendar, etc. • First step in going from raw data to information • Lots of CS theory (121) to help out • Regular expressions (finite state automata) • Context-free grammars (push-down automata) • These abstractions show up in optimization too! • Lots of tool support • E.g., Lex and Yacc; parsing combinators; etc.

  6. Elaboration Type-checking. • Resolve variables, modules, etc. • Check that operations are given values of the right types. • Infer types for sub-expressions. • Check for other safety/security problems. UntypedAbstract Syntax Trees Typed Abstract Syntax Trees

  7. Lowering Translate high-level features into a small number of target-like constructs. • e.g., while, for, do-loops all compiled to code using goto’s. • e.g., objects, closures to records and function pointers. • e.g., make type-tests, array-bounds checks, etc. explicit. Typed Abstract Syntax Trees Intermediate Code ASTs

  8. Optimization Rewrite expensive sequences of operations into less expensive. • e.g., constant folding: 3+4  7 • e.g., lift an invariant computation out of a loop • e.g., parallelize a loop Intermediate Code ASTs optimization Intermediate Code ASTs

  9. Code Generation Translate intermediate code into target code. • Register assignment • Instruction selection • Instruction scheduling • Machine-specific optimization Machine Code Intermediate Code ASTs

  10. Who Should Take 153? • People fascinated by languages & compilers • Why does[n’t] this language include this feature? • Systems programmers • Know the one tool that you use every day. • What can[’t] a compiler do well? • Architecture designers • See 432, itaniumdisasters; register windows • These days, architecture folks use compilers too! • API designers • A language is the ultimate API • c.f., Facebook

  11. What background? • Ideally CS51 & CS61 • But 51 is probably good enough. • 61 is okay, but you will have to pick up Ocaml. • Some assumptions: • Assume you know a little bit about how machines work (e.g., 2’s compliment arithmetic). • If you don’t know something, ask me! • Assume you can write functional programs. • Assume you are willing to work your tail off.

  12. Administrivia • Web site: • http://people.fas.harvard.edu/~lib153/ • TF: Lucas Waye • 9 programming assignments. • Bulk of your grade. • Work with a partner. • No late days. Ever. • Mid-term (Oct 9) and Final exams.

  13. Programming Environment • Ocaml • Not familiar? Pick up along the way or take 51. • Ideal for writing compilers. • SPIM • MIPS simulator. • Ideal target for compilers.

  14. Book Modern Compiler Implementation in ML, by Andrew Appel. Good for background reading, but we won’t follow closely.

  15. Projects • MIPS simulator • Understand the machine we are targeting • Fortran-ish -> MIPS • Simple front-end • Simple lowering & code generation • C-ish -> MIPS • 1st-order procedures, structs, arrays • Scheme-ish -> C-ish • Higher-order procedures, type-tests • ML-ish -> Scheme-ish • Type inference

  16. Projects, continued • Algebraic optimization • Tree-based rewriting • Control-flow graphs • Rip out naïve C-ish backend and replace with one based on control-flow graphs. • Implement liveness analysis • Implement graph-coloring register allocation

  17. Key Outcomes • Understand how compilers work • Parsing, type-checking & inference, lowering, analysis, optimization, code generation. • How to rewrite your code so that the compiler can do its job better. • Significant engineering experience on a big project. • Understand language and architecture design tradeoffs. • e.g., why are error messages in compilers so bad? • e.g., why do advanced languages essentially require garbage collection? • e.g., what prevents us from parallelizing C/C++?

  18. Along the way… • What’s happening with architecture? • Multi-core • Heterogeneous units • What’s happening with languages? • Security may matter more than performance • Productivity may matter more than performance • Cluster-level performance (e.g., Map/Reduce) • Feedback-driven optimization

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