Compilation 2013 Basic Blocks and Traces

Size: px
Start display at page:

Download "Compilation 2013 Basic Blocks and Traces"

Transcription

1 Compilation 2013 Basic Blocks and Traces Erik Ernst Aarhus University

2 IR = Intermediate IR does not match either end perfectly Source: Translation non-trivial, e.g., using the static link Target: & CALL enable side-effects in expressions CJUMP has 2 targets, machine instructions fall through CALL puts returned value in specific register (RV) Why not just drop them? CALL in expression: needed for function : very convenient Strategy: Remove, move CALL 2

3 Idea: Require well-formed IR Trees Type Correct MOVE(TEMP t, ) (MOVE, TEMP t) Satisfies Constraints MOVE(MEM,CALL ) SEQ(MEM,SEQ(,SEQ )) MOVE(BINOP, TEMP s) Only a subset of type correct terms used 3

4 Canonical IR Trees Just ordinary IR trees, but well-formed Requirements: SEQ only topmost (will be removed using exp list) never used Parent of CALL is EXP( ) or MOVE(TEMP t, ) Created in module Canon signature CANON = sig val linearize: stm -> stm list val basicblocks: stm list -> (stm list list * Temp.label) val traceschedule: stm list list Temp.label -> stm list end structure Canon: CANON = struct... end 4

5 Technique: Rewriting Goal of linearize achieved by repeated rewrite Rewriting rules: Specify a from pattern, to be matched Specify a to pattern, to construct from match Correctness requirement: Every possible rewrite preserves the semantics one replaced IR tree by another will be IR tree 5

6 Rewriting 1 Purpose: Eliminate one node Matching: For given IR tree matching concrete nodes, bind subtrees to metavariables Construction: replace metavariables by their values s1 SEQ e s2 e s1 s2 6

7 Rewriting 2 Purpose: Move up BINOP op e2 s BINOP s e1 op e1 e2 MEM((s,e1)) JUMP((s,e1)) CJUMP(op,(s,e1),e2,l1,l2) (s,mem(e1)) (s,jump(e1)) SEQ(s,CJUMP(op,e1,e2,l1,l2)) 7

8 Rewriting 3 Purpose: Pull over operand BINOP MOVE op e1 TEMP e1 s BINOP s e2 t op TEMP e2 t CJUMP(op,e1,(s,e2),l1,l2) SEQ(MOVE(TEMP t,e1),seq(s,cjump(op,temp t,e2,l1,l2) 8

9 Rewriting 4 Purpose: Pull over operand for free BINOP s,e1 commute op e1 s BINOP s e2 op e1 e2 CJUMP(op,e1,(s,e2),l1,l2) s,e1 commute SEQ(s,CJUMP(op,e1,e2,l1,l2)) 9

10 Algorithm Doing the Rewriting Functions do handle deconstruct/reconstruct Functions reorder perform subtree transforms val reorderstm: exp list * (exp list -> stm) -> stm val reorderexp: exp list * (exp list -> exp) -> (stm*exp) fun dostm (T.JUMP(e,labs)) = reorderstm ([e], fn [e] => T.JUMP(e,labs)) dostm (T.CJUMP(p,a,b,t,f)) = reorderstm ([a,b], fn [a,b] => T.CJUMP(p,a,b,t,f)) dostm (T.MOVE(T.TEMP t, b)) = reorderstm ([b], fn [b] => T.MOVE(T.TEMP t, b))... and doexp (T.BINOP(p,a,b)) = reorderexp ([a,b], fn [a,b] => T.BINOP(p,a,b)) doexp (T.MEM(a)) = reorderexp ([a], fn [a] => T.MEM(a))... 10

11 On CALL Problem: A CALL returns result in register RV Why does CALL(f, CALL( ),CALL( )) not work? (unless we are careful) CALL(f,args)) Why does this solve the problem? (MOVE(TEMP t,call(f,args)),temp t) 11

12 After Rewriting 1-4 Stabilizes Eliminate SEQ: First rewrite SEQ to enforce list structure SEQ(SEQ(a,b),c)) Then replace SEQ by list constructor SEQ(a,SEQ(b,c)) SEQ(a,SEQ(b,c)) a::(b::c) fun linearize (stm0: stm): stm list = let definitions of reorderexp, reorderstm, doexp,.. fun linear (T.SEQ(a,b),l) = linear(a,linear(b,l)) linear (s,l) = s::l in linear(dostm stm0, nil) end 12

13 Basic Blocks Control flow: Studying program behavior with no regard to values, just movement (*JUMP, step) Basic block: Sequence of instructions w/o JUMP First statement: LABEL Last statement: [C]JUMP No other LABELs or [C]JUMPs Simple algorithm: at [C]JUMP: end current block; at LABEL: start new blk fixup: add blocks label at very beginning, JUMP to done label at very end Result: basic blocks can be freely reordered 13

14 Traces Trace: instruction sequence that could be executed consecutively (choice: CJUMP) We reorder such that CJUMP is followed by its false label, thus enabling fall through Pseudo-code algorithm: Put all blocks of the program into a list Q. while Q is not empty Start a new (empty) trace, call it T Remove the head element b from Q. while b is not marked Mark b; append b to the end of the current trace T. Examine the successors of b; if there is any unmarked successor c b := c end current trace T. 14

15 Traces May be Optimized All these are correct tracings for the same function prologue statements JUMP (NAME test) LABEL test CJUMP (>,i,n,done,body) LABEL body loop body statements JUMP(NAME test) LABEL done epilogue statements prologue statements JUMP (NAME test) LABEL test CJUMP(<=,i,N,done,body) LABEL done epilogue statements LABEL body loop body statements JUMP(NAME test) Count instructions for the loop Optimal traces: not this compiler prologue statements JUMP (NAME test) LABEL body loop body statements JUMP(NAME test) LABEL test CJUMP (>,i,n,done,body) LABEL done epilogue statements 15

16 Implementation File canon.sml available, fully implemented Has signature CANON (including linearize, basicblocks, traceschedule) Note warnings during compilation: canon.sml: Warning: match nonexhaustive e :: nil =>... canon.sml: Warning: match nonexhaustive a :: b :: nil =>... Not a problem ;-) Caused by using well-formed subset of type correct trees, carefully.. 16

17 Summary IR trees really intermediate: Not a perfect fit for source, nor for target For target: Eliminate & SEQ, move CALL, ensure parent EXP( ) or MOVE(TEMP t, ) Transformations: Move up, eliminate an, pull over expression, ditto for free Tricky algorithm: note deconstruct/reconstruct Protect register RV: Transform CALL Move CALL up to EXP/MOVE Basic blocks: find, then reorder into traces Translation to IR 17

Compiler Construction 2009/2010: Intermediate Representation

Compiler Construction 2009/2010: Intermediate Representation Compiler Construction 2009/2010: Intermediate Representation Annette Bieniusa November 24, 2009 Outline 1 Contexts 2 Canonical Trees Using Expressions in different Contexts Compare the translation for

More information

Itree Stmts and Exprs. Back-End Code Generation. Summary: IR -> Machine Code. Side-Effects

Itree Stmts and Exprs. Back-End Code Generation. Summary: IR -> Machine Code. Side-Effects Back-End Code Generation Given a list of itree fragments, how to generate the corresponding assembly code? datatype frag = PROC of {name : Tree.label, function name body : Tree.stm, function body itree

More information

Compilation 2013 Translation to IR

Compilation 2013 Translation to IR Compilation 2013 Erik Ernst Aarhus University Intermediate Representation Translation source/target uses IR as a bridge Simplification: n+m combinations, not n m Java SML Pascal C C++ SPARC MIPS Pentium

More information

Topic 7: Intermediate Representations

Topic 7: Intermediate Representations Topic 7: Intermediate Representations COS 320 Compiling Techniques Princeton University Spring 2016 Lennart Beringer 1 2 Intermediate Representations 3 Intermediate Representations 4 Intermediate Representations

More information

CPSC 411, Fall 2010 Midterm Examination

CPSC 411, Fall 2010 Midterm Examination CPSC 411, Fall 2010 Midterm Examination. Page 1 of 11 CPSC 411, Fall 2010 Midterm Examination Name: Q1: 10 Q2: 15 Q3: 15 Q4: 10 Q5: 10 60 Please do not open this exam until you are told to do so. But please

More information

Compiler Internals. Reminders. Course infrastructure. Registering for the course

Compiler Internals. Reminders. Course infrastructure. Registering for the course Compiler Internals 15-745 Optimizing Compilers Spring 2006 Peter Lee Reminders Get on the course mailing list Check out the web site http://www.cs.cmu.edu/afs/cs/ academic/class/15745-s06/web subscribe

More information

7 Translation to Intermediate Code

7 Translation to Intermediate Code 7 Translation to Intermediate Code ( 7. Translation to Intermediate Code, p. 150) This chpater marks the transition from the source program analysis phase to the target program synthesis phase. All static

More information

Administration. Where we are. Canonical form. Canonical form. One SEQ node. CS 412 Introduction to Compilers

Administration. Where we are. Canonical form. Canonical form. One SEQ node. CS 412 Introduction to Compilers Administration CS 412 Introduction to Compilers Andrew Myers Cornell University Lecture 15: Canonical IR 26 Feb 01 HW3 due Friday Prelim 1 next Tuesday evening (7:30-9:30PM) location TBA covers topics

More information

A Third Look At ML. Chapter Nine Modern Programming Languages, 2nd ed. 1

A Third Look At ML. Chapter Nine Modern Programming Languages, 2nd ed. 1 A Third Look At ML Chapter Nine Modern Programming Languages, 2nd ed. 1 Outline More pattern matching Function values and anonymous functions Higher-order functions and currying Predefined higher-order

More information

CPSC 411, 2015W Term 2 Midterm Exam Date: February 25, 2016; Instructor: Ron Garcia

CPSC 411, 2015W Term 2 Midterm Exam Date: February 25, 2016; Instructor: Ron Garcia CPSC 411, 2015W Term 2 Midterm Exam Date: February 25, 2016; Instructor: Ron Garcia This is a closed book exam; no notes; no calculators. Answer in the space provided. There are 8 questions on 14 pages,

More information

Languages and Compiler Design II IR Code Generation I

Languages and Compiler Design II IR Code Generation I Languages and Compiler Design II IR Code Generation I Material provided by Prof. Jingke Li Stolen with pride and modified by Herb Mayer PSU Spring 2010 rev.: 4/16/2010 PSU CS322 HM 1 Agenda Grammar G1

More information

IR trees: Statements. IR trees: Expressions. Translating MiniJava. Kinds of expressions. Local variables: Allocate as a temporary t

IR trees: Statements. IR trees: Expressions. Translating MiniJava. Kinds of expressions. Local variables: Allocate as a temporary t IR trees: Expressions CONST Integer constant i i NAME Symbolic constant n [a code label] n TEMP Temporary t [one of any number of registers ] t BINOP Application of binary operator: e 1 e 2 ADD, SUB, MUL,

More information

CSE341 Spring 2016, Midterm Examination April 29, 2016

CSE341 Spring 2016, Midterm Examination April 29, 2016 CSE341 Spring 2016, Midterm Examination April 29, 2016 Please do not turn the page until 10:30. Rules: The exam is closed-book, closed-note, etc. except for one side of one 8.5x11in piece of paper. Please

More information

Administration. Today

Administration. Today Announcements Administration Office hour today changed to 3:30 4:30 Class is cancelled next Monday I have to attend a Senate Curriculum Committee meeting Project Build a Functions compiler from the Expressions

More information

Where we are. What makes a good IR? Intermediate Code. CS 4120 Introduction to Compilers

Where we are. What makes a good IR? Intermediate Code. CS 4120 Introduction to Compilers Where we are CS 4120 Introduction to Compilers Andrew Myers Cornell University Lecture 13: Intermediate Code 25 Sep 09 Source code (character stream) Token stream Abstract syntax tree Abstract syntax tree

More information

CSE341 Spring 2016, Midterm Examination April 29, 2016

CSE341 Spring 2016, Midterm Examination April 29, 2016 CSE341 Spring 2016, Midterm Examination April 29, 2016 Please do not turn the page until 10:30. Rules: The exam is closed-book, closed-note, etc. except for one side of one 8.5x11in piece of paper. Please

More information

Intermediate Code Generation

Intermediate Code Generation Intermediate Code Generation In the analysis-synthesis model of a compiler, the front end analyzes a source program and creates an intermediate representation, from which the back end generates target

More information

Metaprogramming assignment 3

Metaprogramming assignment 3 Metaprogramming assignment 3 Optimising embedded languages Due at noon on Thursday 29th November 2018 This exercise uses the BER MetaOCaml compiler, which you can install via opam. The end of this document

More information

Announcements. Project 2: released due this sunday! Midterm date is now set: check newsgroup / website. Chapter 7: Translation to IR

Announcements. Project 2: released due this sunday! Midterm date is now set: check newsgroup / website. Chapter 7: Translation to IR Announcements Project 2: released due this sunday! Midterm date is now set: check newsgroup / website. 1 Translation to Intermediate Code (Chapter 7) This stage converts an AST into an intermediate representation.

More information

CSE341, Fall 2011, Midterm Examination October 31, 2011

CSE341, Fall 2011, Midterm Examination October 31, 2011 CSE341, Fall 2011, Midterm Examination October 31, 2011 Please do not turn the page until the bell rings. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

Processadors de Llenguatge II. Functional Paradigm. Pratt A.7 Robert Harper s SML tutorial (Sec II)

Processadors de Llenguatge II. Functional Paradigm. Pratt A.7 Robert Harper s SML tutorial (Sec II) Processadors de Llenguatge II Functional Paradigm Pratt A.7 Robert Harper s SML tutorial (Sec II) Rafael Ramirez Dep Tecnologia Universitat Pompeu Fabra Paradigm Shift Imperative Paradigm State Machine

More information

Programming Language Processor Theory

Programming Language Processor Theory Programming Language Processor Theory Munehiro Takimoto Course Descriptions Method of Evaluation: made through your technical reports Purposes: understanding various theories and implementations of modern

More information

CS 352 Compilers: Principles and Practice Final Examination, 12/11/05

CS 352 Compilers: Principles and Practice Final Examination, 12/11/05 CS 352 Compilers: Principles and Practice Final Examination, 12/11/05 Instructions: Read carefully through the whole exam first and plan your time. Note the relative weight of each question and part (as

More information

COS 320. Compiling Techniques

COS 320. Compiling Techniques Topic 5: Types COS 320 Compiling Techniques Princeton University Spring 2016 Lennart Beringer 1 Types: potential benefits (I) 2 For programmers: help to eliminate common programming mistakes, particularly

More information

Compiler Optimization Techniques

Compiler Optimization Techniques Compiler Optimization Techniques Department of Computer Science, Faculty of ICT February 5, 2014 Introduction Code optimisations usually involve the replacement (transformation) of code from one sequence

More information

Standard ML. Data types. ML Datatypes.1

Standard ML. Data types. ML Datatypes.1 Standard ML Data types ML Datatypes.1 Concrete Datatypes The datatype declaration creates new types These are concrete data types, not abstract Concrete datatypes can be inspected - constructed and taken

More information

Notes on specifying user defined types

Notes on specifying user defined types Notes on specifying user defined types data Exp = While Exp Exp Bool Bool If Exp Exp Exp Int Int Add Exp Exp Sub Exp Exp Mul Exp Exp Div Exp Exp Leq Exp Exp Char Char Ceq Exp Exp Pair Exp Exp Fst Exp Snd

More information

A Second Look At ML. Chapter Seven Modern Programming Languages, 2nd ed. 1

A Second Look At ML. Chapter Seven Modern Programming Languages, 2nd ed. 1 A Second Look At ML Chapter Seven Modern Programming Languages, 2nd ed. 1 Outline Patterns Local variable definitions A sorting example Chapter Seven Modern Programming Languages, 2nd ed. 2 Two Patterns

More information

Introduction to ML. Mooly Sagiv. Cornell CS 3110 Data Structures and Functional Programming

Introduction to ML. Mooly Sagiv. Cornell CS 3110 Data Structures and Functional Programming Introduction to ML Mooly Sagiv Cornell CS 3110 Data Structures and Functional Programming Typed Lambda Calculus Chapter 9 Benjamin Pierce Types and Programming Languages Call-by-value Operational Semantics

More information

CSE341 Section 3. Standard-Library Docs, First-Class Functions, & More

CSE341 Section 3. Standard-Library Docs, First-Class Functions, & More CSE341 Section 3 Standard-Library Docs, First-Class Functions, & More Adapted from slides by Daniel Snitkovskiy, Nick Mooney, Nicholas Shahan, Patrick Larson, and Dan Grossman Agenda 1. SML Docs Standard

More information

Abstraction Functions and Representation Invariants

Abstraction Functions and Representation Invariants Abstraction Functions and Representation Invariants Prof. Clarkson Fall 2017 Today s music: In C by Terry Riley A2 Implement a text adventure game engine, and write your own adventure Experience with lists,

More information

Exercises on ML. Programming Languages. Chanseok Oh

Exercises on ML. Programming Languages. Chanseok Oh Exercises on ML Programming Languages Chanseok Oh chanseok@cs.nyu.edu Dejected by an arcane type error? - foldr; val it = fn : ('a * 'b -> 'b) -> 'b -> 'a list -> 'b - foldr (fn x=> fn y => fn z => (max

More information

Pattern Matching and Abstract Data Types

Pattern Matching and Abstract Data Types Pattern Matching and Abstract Data Types Tom Murphy VII 3 Dec 2002 0-0 Outline Problem Setup Views ( Views: A Way For Pattern Matching To Cohabit With Data Abstraction, Wadler, 1986) Active Patterns (

More information

CS153: Compilers Lecture 17: Control Flow Graph and Data Flow Analysis

CS153: Compilers Lecture 17: Control Flow Graph and Data Flow Analysis CS153: Compilers Lecture 17: Control Flow Graph and Data Flow Analysis Stephen Chong https://www.seas.harvard.edu/courses/cs153 Announcements Project 5 out Due Tuesday Nov 13 (14 days) Project 6 out Due

More information

Programming in Standard ML: Continued

Programming in Standard ML: Continued Programming in Standard ML: Continued Specification and Verification with Higher-Order Logic Arnd Poetzsch-Heffter (Slides by Jens Brandt) Software Technology Group Fachbereich Informatik Technische Universität

More information

Interpreters and Tail Calls Fall 2017 Discussion 8: November 1, 2017 Solutions. 1 Calculator. calc> (+ 2 2) 4

Interpreters and Tail Calls Fall 2017 Discussion 8: November 1, 2017 Solutions. 1 Calculator. calc> (+ 2 2) 4 CS 61A Interpreters and Tail Calls Fall 2017 Discussion 8: November 1, 2017 Solutions 1 Calculator We are beginning to dive into the realm of interpreting computer programs that is, writing programs that

More information

Intermediate Code Generation. Intermediate Representations (IR) Case Study : itree. itree Statements and Expressions

Intermediate Code Generation. Intermediate Representations (IR) Case Study : itree. itree Statements and Expressions Intermediate Code Generation Translating the abstract syntax into the intermediate representation. report all lexical & syntactic errors report all semantic errors Intermediate Representations (IR) What

More information

Topic 3: Syntax Analysis I

Topic 3: Syntax Analysis I Topic 3: Syntax Analysis I Compiler Design Prof. Hanjun Kim CoreLab (Compiler Research Lab) POSTECH 1 Back-End Front-End The Front End Source Program Lexical Analysis Syntax Analysis Semantic Analysis

More information

Lecture 5: Declarative Programming. The Declarative Kernel Language Machine. September 12th, 2011

Lecture 5: Declarative Programming. The Declarative Kernel Language Machine. September 12th, 2011 Lecture 5: Declarative Programming. The Declarative Kernel Language Machine September 12th, 2011 1 Lecture Outline Declarative Programming contd Dataflow Variables contd Expressions and Statements Functions

More information

regsim.scm ~/umb/cs450/ch5.base/ 1 11/11/13

regsim.scm ~/umb/cs450/ch5.base/ 1 11/11/13 1 File: regsim.scm Register machine simulator from section 5.2 of STRUCTURE AND INTERPRETATION OF COMPUTER PROGRAMS This file can be loaded into Scheme as a whole. Then you can define and simulate machines

More information

CSE341 Autumn 2017, Midterm Examination October 30, 2017

CSE341 Autumn 2017, Midterm Examination October 30, 2017 CSE341 Autumn 2017, Midterm Examination October 30, 2017 Please do not turn the page until 2:30. Rules: The exam is closed-book, closed-note, etc. except for one side of one 8.5x11in piece of paper. Please

More information

Handout 2 August 25, 2008

Handout 2 August 25, 2008 CS 502: Compiling and Programming Systems Handout 2 August 25, 2008 Project The project you will implement will be a subset of Standard ML called Mini-ML. While Mini- ML shares strong syntactic and semantic

More information

CIS 341 Midterm February 28, Name (printed): Pennkey (login id): SOLUTIONS

CIS 341 Midterm February 28, Name (printed): Pennkey (login id): SOLUTIONS CIS 341 Midterm February 28, 2013 Name (printed): Pennkey (login id): My signature below certifies that I have complied with the University of Pennsylvania s Code of Academic Integrity in completing this

More information

Lists. Michael P. Fourman. February 2, 2010

Lists. Michael P. Fourman. February 2, 2010 Lists Michael P. Fourman February 2, 2010 1 Introduction The list is a fundamental datatype in most functional languages. ML is no exception; list is a built-in ML type constructor. However, to introduce

More information

CODE GENERATION Monday, May 31, 2010

CODE GENERATION Monday, May 31, 2010 CODE GENERATION memory management returned value actual parameters commonly placed in registers (when possible) optional control link optional access link saved machine status local data temporaries A.R.

More information

CS 2210 Programming Project (Part IV)

CS 2210 Programming Project (Part IV) CS 2210 Programming Project (Part IV) April 25, 2018 Code Generation This project is intended to give you experience in writing a code generator as well as bring together the various issues of code generation

More information

CS4410 : Spring 2013

CS4410 : Spring 2013 CS4410 : Spring 2013 Next PS: Map Fish code to MIPS code Issues: eliminating compound expressions eliminating variables encoding conditionals, short- circuits, loops type exp = Var of var Int of int Binop

More information

CSE341, Fall 2011, Midterm Examination October 31, 2011

CSE341, Fall 2011, Midterm Examination October 31, 2011 CSE341, Fall 2011, Midterm Examination October 31, 2011 Please do not turn the page until the bell rings. Rules: The exam is closed-book, closed-note, except for one side of one 8.5x11in piece of paper.

More information

Principles of Programming Languages COMP251: Syntax and Grammars

Principles of Programming Languages COMP251: Syntax and Grammars Principles of Programming Languages COMP251: Syntax and Grammars Prof. Dekai Wu Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong, China Fall 2007

More information

CS293S Redundancy Removal. Yufei Ding

CS293S Redundancy Removal. Yufei Ding CS293S Redundancy Removal Yufei Ding Review of Last Class Consideration of optimization Sources of inefficiency Components of optimization Paradigms of optimization Redundancy Elimination Types of intermediate

More information

Lecture 19: Signatures, Structures, and Type Abstraction

Lecture 19: Signatures, Structures, and Type Abstraction 15-150 Lecture 19: Signatures, Structures, and Type Abstraction Lecture by Dan Licata March 27, 2012 In these lectures, we will discuss the use of the ML module system for structuring large programs. Key

More information

Recap from last time. Programming Languages. CSE 130 : Fall Lecture 3: Data Types. Put it together: a filter function

Recap from last time. Programming Languages. CSE 130 : Fall Lecture 3: Data Types. Put it together: a filter function CSE 130 : Fall 2011 Recap from last time Programming Languages Lecture 3: Data Types Ranjit Jhala UC San Diego 1 2 A shorthand for function binding Put it together: a filter function # let neg = fun f

More information

Fundamentals of Compilation

Fundamentals of Compilation PART ONE Fundamentals of Compilation 1 Introduction A compiler was originally a program that compiled subroutines [a link-loader]. When in 1954 the combination algebraic compiler came into use, or rather

More information

Chapter 3: Describing Syntax and Semantics. Introduction Formal methods of describing syntax (BNF)

Chapter 3: Describing Syntax and Semantics. Introduction Formal methods of describing syntax (BNF) Chapter 3: Describing Syntax and Semantics Introduction Formal methods of describing syntax (BNF) We can analyze syntax of a computer program on two levels: 1. Lexical level 2. Syntactic level Lexical

More information

Agenda. CSE P 501 Compilers. Big Picture. Compiler Organization. Intermediate Representations. IR for Code Generation. CSE P 501 Au05 N-1

Agenda. CSE P 501 Compilers. Big Picture. Compiler Organization. Intermediate Representations. IR for Code Generation. CSE P 501 Au05 N-1 Agenda CSE P 501 Compilers Instruction Selection Hal Perkins Autumn 2005 Compiler back-end organization Low-level intermediate representations Trees Linear Instruction selection algorithms Tree pattern

More information

CSE341: Programming Languages Lecture 17 Implementing Languages Including Closures. Dan Grossman Autumn 2018

CSE341: Programming Languages Lecture 17 Implementing Languages Including Closures. Dan Grossman Autumn 2018 CSE341: Programming Languages Lecture 17 Implementing Languages Including Closures Dan Grossman Autumn 2018 Typical workflow concrete syntax (string) "(fn x => x + x) 4" Parsing Possible errors / warnings

More information

CIS 341 Final Examination 4 May 2017

CIS 341 Final Examination 4 May 2017 CIS 341 Final Examination 4 May 2017 1 /14 2 /15 3 /12 4 /14 5 /34 6 /21 7 /10 Total /120 Do not begin the exam until you are told to do so. You have 120 minutes to complete the exam. There are 14 pages

More information

CMPT 379 Compilers. Parse trees

CMPT 379 Compilers. Parse trees CMPT 379 Compilers Anoop Sarkar http://www.cs.sfu.ca/~anoop 10/25/07 1 Parse trees Given an input program, we convert the text into a parse tree Moving to the backend of the compiler: we will produce intermediate

More information

OCaml. ML Flow. Complex types: Lists. Complex types: Lists. The PL for the discerning hacker. All elements must have same type.

OCaml. ML Flow. Complex types: Lists. Complex types: Lists. The PL for the discerning hacker. All elements must have same type. OCaml The PL for the discerning hacker. ML Flow Expressions (Syntax) Compile-time Static 1. Enter expression 2. ML infers a type Exec-time Dynamic Types 3. ML crunches expression down to a value 4. Value

More information

6.001 Notes: Section 15.1

6.001 Notes: Section 15.1 6.001 Notes: Section 15.1 Slide 15.1.1 Our goal over the next few lectures is to build an interpreter, which in a very basic sense is the ultimate in programming, since doing so will allow us to define

More information

Compilation 2013 Semantic Analysis

Compilation 2013 Semantic Analysis Compilation 2013 Semantic Analysis Erik Ernst Aarhus University Semantic Analysis The meaning of a program: Above the contextfree level Use general programming to compute well-formedness representation

More information

All the operations used in the expression are over integers. a takes a pair as argument. (a pair is also a tuple, or more specifically, a 2-tuple)

All the operations used in the expression are over integers. a takes a pair as argument. (a pair is also a tuple, or more specifically, a 2-tuple) Weekly exercises in INF3110 week 41 6-10.10.2008 Exercise 1 Exercise 6.1 in Mitchell's book a) fun a(x,y) = x+2*y; val a = fn : int * int -> int All the operations used in the expression are over integers.

More information

L28: Advanced functional programming

L28: Advanced functional programming L28: Advanced functional programming Exercise 2 Due on 8th March 2017 Submission instructions Your solutions for this exericse should be handed in to the Graduate Education Office by 4pm on the due date.

More information

CSE 413 Languages & Implementation. Hal Perkins Winter 2019 Structs, Implementing Languages (credits: Dan Grossman, CSE 341)

CSE 413 Languages & Implementation. Hal Perkins Winter 2019 Structs, Implementing Languages (credits: Dan Grossman, CSE 341) CSE 413 Languages & Implementation Hal Perkins Winter 2019 Structs, Implementing Languages (credits: Dan Grossman, CSE 341) 1 Goals Representing programs as data Racket structs as a better way to represent

More information

CSE413: Programming Languages and Implementation Racket structs Implementing languages with interpreters Implementing closures

CSE413: Programming Languages and Implementation Racket structs Implementing languages with interpreters Implementing closures CSE413: Programming Languages and Implementation Racket structs Implementing languages with interpreters Implementing closures Dan Grossman Fall 2014 Hi! I m not Hal J I love this stuff and have taught

More information

CSE 504: Compiler Design. Instruction Selection

CSE 504: Compiler Design. Instruction Selection Instruction Selection Pradipta De pradipta.de@sunykorea.ac.kr Current Topic Instruction Selection techniques Tree Walk Tiling based approach Peephole Optimization Instruction Selection Difficulty of Instruction

More information

CMSC 330: Organization of Programming Languages. Formal Semantics of a Prog. Lang. Specifying Syntax, Semantics

CMSC 330: Organization of Programming Languages. Formal Semantics of a Prog. Lang. Specifying Syntax, Semantics Recall Architecture of Compilers, Interpreters CMSC 330: Organization of Programming Languages Source Scanner Parser Static Analyzer Operational Semantics Intermediate Representation Front End Back End

More information

Acknowledgement. CS Compiler Design. Intermediate representations. Intermediate representations. Semantic Analysis - IR Generation

Acknowledgement. CS Compiler Design. Intermediate representations. Intermediate representations. Semantic Analysis - IR Generation Acknowledgement CS3300 - Compiler Design Semantic Analysis - IR Generation V. Krishna Nandivada IIT Madras Copyright c 2000 by Antony L. Hosking. Permission to make digital or hard copies of part or all

More information

Scheme Basics > (butfirst '(help!)) ()

Scheme Basics > (butfirst '(help!)) () Scheme Basics > (butfirst '(help!)) () [The butfirst of a *sentence* containing one word is all but that word, i.e., the empty sentence. (BUTFIRST 'HELP!) without the inner parentheses would be butfirst

More information

Intermediate Representations

Intermediate Representations Intermediate Representations Akim Demaille Étienne Renault Roland Levillain first.last@lrde.epita.fr EPITA École Pour l Informatique et les Techniques Avancées April 18, 2017 Intermediate Representations

More information

INTERPRETERS 8. 1 Calculator COMPUTER SCIENCE 61A. November 3, 2016

INTERPRETERS 8. 1 Calculator COMPUTER SCIENCE 61A. November 3, 2016 INTERPRETERS 8 COMPUTER SCIENCE 61A November 3, 2016 1 Calculator We are beginning to dive into the realm of interpreting computer programs that is, writing programs that understand other programs. In

More information

Compilers. Intermediate representations and code generation. Yannis Smaragdakis, U. Athens (original slides by Sam

Compilers. Intermediate representations and code generation. Yannis Smaragdakis, U. Athens (original slides by Sam Compilers Intermediate representations and code generation Yannis Smaragdakis, U. Athens (original slides by Sam Guyer@Tufts) Today Intermediate representations and code generation Scanner Parser Semantic

More information

Lecture 21: Red-Black Trees

Lecture 21: Red-Black Trees 15-150 Lecture 21: Red-Black Trees Lecture by Dan Licata April 3, 2012 Last time, we talked about the signature for dictionaries: signature ORDERED = sig type t val compare : t * t -> order signature DICT

More information

IR Lowering. Notation. Lowering Methodology. Nested Expressions. Nested Statements CS412/CS413. Introduction to Compilers Tim Teitelbaum

IR Lowering. Notation. Lowering Methodology. Nested Expressions. Nested Statements CS412/CS413. Introduction to Compilers Tim Teitelbaum IR Lowering CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 19: Efficient IL Lowering 7 March 07 Use temporary variables for the translation Temporary variables in the Low IR store intermediate

More information

Dynamic Types , Spring March 21, 2017

Dynamic Types , Spring March 21, 2017 Dynamic Types 15-312, Spring 2017 March 21, 2017 Announcements Homework 4 will be released shortly. Most of it is new, so it s hard to tell how hard we made it. Please start early! Look at what I made

More information

CPS Conversion. Di Zhao.

CPS Conversion. Di Zhao. CPS Conversion Di Zhao zhaodi01@mail.ustc.edu.cn This is the first assignment of the course - Advanced Topics in Software Technologies in the 2014-2015 academic year. During this course, we will explore

More information

CS Lecture 2. The Front End. Lecture 2 Lexical Analysis

CS Lecture 2. The Front End. Lecture 2 Lexical Analysis CS 1622 Lecture 2 Lexical Analysis CS 1622 Lecture 2 1 Lecture 2 Review of last lecture and finish up overview The first compiler phase: lexical analysis Reading: Chapter 2 in text (by 1/18) CS 1622 Lecture

More information

CSE100 Lecture03 Machines, Instructions, and Programs Introduction to Computer Systems

CSE100 Lecture03 Machines, Instructions, and Programs Introduction to Computer Systems Machines, Instructions, and Introduction to Computer Systems M.A. Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka 1000, Bangladesh CSE, BUET, 2009 MARIE Machine

More information

Staging (part II) March 2018

Staging (part II) March 2018 Staging (part II) March 2018 .. Last time: staging This time: more staging.. Generalizing algebraic optmisation Staging and effects Review: staging Multi-stage programming adds support for building

More information

8. Write an example for expression tree. [A/M 10] (A+B)*((C-D)/(E^F))

8. Write an example for expression tree. [A/M 10] (A+B)*((C-D)/(E^F)) DHANALAKSHMI COLLEGE OF ENGINEERING DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING EC6301 OBJECT ORIENTED PROGRAMMING AND DATA STRUCTURES UNIT IV NONLINEAR DATA STRUCTURES Part A 1. Define Tree [N/D 08]

More information

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE TED (10)-3071 Reg. No.. (REVISION-2010) Signature. FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE (Common to CT and IF) [Time: 3 hours (Maximum marks: 100)

More information

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 19: Efficient IL Lowering 5 March 08

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 19: Efficient IL Lowering 5 March 08 CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 19: Efficient IL Lowering 5 March 08 CS 412/413 Spring 2008 Introduction to Compilers 1 IR Lowering Use temporary variables for the translation

More information

Summer 2017 Discussion 10: July 25, Introduction. 2 Primitives and Define

Summer 2017 Discussion 10: July 25, Introduction. 2 Primitives and Define CS 6A Scheme Summer 207 Discussion 0: July 25, 207 Introduction In the next part of the course, we will be working with the Scheme programming language. In addition to learning how to write Scheme programs,

More information

Compilers. Compiler Construction Tutorial The Front-end

Compilers. Compiler Construction Tutorial The Front-end Compilers Compiler Construction Tutorial The Front-end Salahaddin University College of Engineering Software Engineering Department 2011-2012 Amanj Sherwany http://www.amanj.me/wiki/doku.php?id=teaching:su:compilers

More information

PAIRS AND LISTS 6. GEORGE WANG Department of Electrical Engineering and Computer Sciences University of California, Berkeley

PAIRS AND LISTS 6. GEORGE WANG Department of Electrical Engineering and Computer Sciences University of California, Berkeley PAIRS AND LISTS 6 GEORGE WANG gswang.cs61a@gmail.com Department of Electrical Engineering and Computer Sciences University of California, Berkeley June 29, 2010 1 Pairs 1.1 Overview To represent data types

More information

Three address representation

Three address representation Three address representation A typical inetrnal representation is three address ce. In many cases, the compound statements (e.g. for or do loops and if statements) are transformed into sequences of instructions

More information

We ve written these as a grammar, but the grammar also stands for an abstract syntax tree representation of the IR.

We ve written these as a grammar, but the grammar also stands for an abstract syntax tree representation of the IR. CS 4120 Lecture 14 Syntax-directed translation 26 September 2011 Lecturer: Andrew Myers We want to translate from a high-level programming into an intermediate representation (IR). This lecture introduces

More information

Lecture 6: The Declarative Kernel Language Machine. September 13th, 2011

Lecture 6: The Declarative Kernel Language Machine. September 13th, 2011 Lecture 6: The Declarative Kernel Language Machine September 13th, 2011 Lecture Outline Computations contd Execution of Non-Freezable Statements on the Abstract Machine The skip Statement The Sequential

More information

MIT Introduction to Program Analysis and Optimization. Martin Rinard Laboratory for Computer Science Massachusetts Institute of Technology

MIT Introduction to Program Analysis and Optimization. Martin Rinard Laboratory for Computer Science Massachusetts Institute of Technology MIT 6.035 Introduction to Program Analysis and Optimization Martin Rinard Laboratory for Computer Science Massachusetts Institute of Technology Program Analysis Compile-time reasoning about run-time behavior

More information

Redefinition of an identifier is OK, but this is redefinition not assignment; Thus

Redefinition of an identifier is OK, but this is redefinition not assignment; Thus Redefinition of an identifier is OK, but this is redefinition not assignment; Thus val x = 100; val x = (x=100); is fine; there is no type error even though the first x is an integer and then it is a boolean.

More information

PART ONE Fundamentals of Compilation

PART ONE Fundamentals of Compilation PART ONE Fundamentals of Compilation 1 Introduction A compiler was originally a program that compiled subroutines [a link-loader]. When in 1954the combination algebraic compiler came into use, or rather

More information

Stacks, Queues and Hierarchical Collections

Stacks, Queues and Hierarchical Collections Programming III Stacks, Queues and Hierarchical Collections 2501ICT Nathan Contents Linked Data Structures Revisited Stacks Queues Trees Binary Trees Generic Trees Implementations 2 Copyright 2002- by

More information

UNIT-3. (if we were doing an infix to postfix translator) Figure: conceptual view of syntax directed translation.

UNIT-3. (if we were doing an infix to postfix translator) Figure: conceptual view of syntax directed translation. UNIT-3 SYNTAX-DIRECTED TRANSLATION: A Grammar symbols are associated with attributes to associate information with the programming language constructs that they represent. Values of these attributes are

More information

MIDTERM EXAMINATION Spring 2010 CS301- Data Structures

MIDTERM EXAMINATION Spring 2010 CS301- Data Structures MIDTERM EXAMINATION Spring 2010 CS301- Data Structures Question No: 1 Which one of the following statement is NOT correct. In linked list the elements are necessarily to be contiguous In linked list the

More information

CS 61c: Great Ideas in Computer Architecture

CS 61c: Great Ideas in Computer Architecture MIPS Functions July 1, 2014 Review I RISC Design Principles Smaller is faster: 32 registers, fewer instructions Keep it simple: rigid syntax, fixed instruction length MIPS Registers: $s0-$s7,$t0-$t9, $0

More information

Principles of Functional Programming

Principles of Functional Programming 15-150 Principles of Functional Programming Some Slides for Lecture 16 Modules March 20, 2018 Michael Erdmann Signatures & Structures A signature specifies an interface. A structure provides an implementation.

More information

CSC324- TUTORIAL 5. Shems Saleh* *Some slides inspired by/based on Afsaneh Fazly s slides

CSC324- TUTORIAL 5. Shems Saleh* *Some slides inspired by/based on Afsaneh Fazly s slides CSC324- TUTORIAL 5 ML Shems Saleh* *Some slides inspired by/based on Afsaneh Fazly s slides Assignment 1 2 More questions were added Questions regarding the assignment? Starting ML Who am I? Shems Saleh

More information

Goals of Program Optimization (1 of 2)

Goals of Program Optimization (1 of 2) Goals of Program Optimization (1 of 2) Goal: Improve program performance within some constraints Ask Three Key Questions for Every Optimization 1. Is it legal? 2. Is it profitable? 3. Is it compile-time

More information

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming Closures Mooly Sagiv Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming t ::= x x. t t t Call-by-value big-step Operational Semantics terms variable v ::= values abstraction x.

More information

CSE341 Spring 2017, Midterm Examination April 28, 2017

CSE341 Spring 2017, Midterm Examination April 28, 2017 CSE341 Spring 2017, Midterm Examination April 28, 2017 Please do not turn the page until 12:30. Rules: The exam is closed-book, closed-note, etc. except for one side of one 8.5x11in piece of paper. Please

More information