Case Studies of Compilers and Future Trends Chapter 21 Mooly Sagiv

Case Studies of Compilers and Future Trends

Chapter 21

Mooly Sagiv

Goals

• Learn on exiting compilers– Which of the studied subjects implemented – Mention techniques not studied

• Future trends (textbook)

• Other trends

• Techniques used in optimizing compilers

• Have some fun

Compilers Studied

• SUN compilers for SPARC 8, 9

• IBM XL compilers for Power and PoewerPC architectures

• Digital compiler for Alpha

• Intel reference compiler for 386

• Comparison criteria– Duration and history– Structure– Optimizations performed on two programs

int length, width, radius;

enum figure {RECTANGLE, CIRCLE} ;

main()

{ int area=0, volume=0; height;

enum figure kind=RECTANGLE;

for (height=0; height < 10; height++)

{if (kind == RECTANGLE) {

area += length * width;

volume += length * width * height; }

else if (kind==CIRCLE){

area += 3.14 * radius * radius ;

volume += 3.14 * radius * height; }

}

process(area, volume);

}

integer a(500, 500), k, l;

do 20 k=1,500

do 20 l=1,500

a(k, l)= k+l

20 continue

call s1(a, 500)

end

subroutine s1(a,n)

integer a(500, 500), n

do 100 i = 1 1,n

do 100 j = i + 1, n

do 100 k = 1, n

l = a(k, i)

m = a(k, j)

a(k, j) = l + m

100 continue

end

The SPARC Architecture• Sparc 8

– 32 bit RISC superscalar system with pipeline– integer and floating point units

– 8 general purpose integer registers (r00)

– load, store, arithmetic, shift, branch, call and system control

– addresses (register+register, register+displ.)– Three address instructions– Several 24 register windows (spilling by OS)

• Sparc 9– 64 bit architecture (upward compatible)

The Sun SPARC Compilers

• Front-ends for C, C++, Fortran 77, Pascal

• Originated from Berkeley 4.2 BSD Unix

• Developed at Sun since 1982

• Original backend for Motorola 68010

• Migrated to M6800 and then to SPARC

• Global optimization developed at 1984

• Interprocedural optimization began at 1984

• Mixed compiler model

The Sun SPARC CompilerFront-End

Sun IR

yabe

Automatic inliner

aliaser

iropt

(global optimizer)

Sun IR

Code generator

Relocatable

Relocatable

ENTRY “s1_” {IS_EXT_ENTRY, ENTRY_IS_GLOBAL}

goto LAB_32

LAB_32: LTEMP.1 = (.n { ACCESS V41} );

i = 1

CBRANCH (i <= LTEMP.1, 1: LAB_36, 0: LAB_35);

LAB_36: LTEMP.2 = (.n { ACCESS V41} );

j=i+1

CBRANCH (j <= LTEMP.2, 1: LAB_41, 0: LAB_40);

LAB_41: LTEMP.3 = (.n { ACCESS V41} );

k=1

CBRANCH (k <= LTEMP.3, 1: LAB_46, 0: LAB_45);

LAB_46: l = (.a[k, i] ACCESS V20} );

m = (.a[k, j] ACCESS V20});

*(a[k,j] = l+m {ACCESS V20, INT});

LAB_34: k = k+1;

CBRANCH(k>LEMP.3, 1: LAB_45, 0: LAB_46);

LAB_45: j=j+1 …

LAB_35:

SUNOptimization Levels• O1 Limited optimizations • O2

– Optimize expressions not involving global, aliased local, and volatile variables

• O3 Worst case assumptions on pointer aliases– Automatic inlining

– software pipelining

– loop unrolling

– instruction scheduling

• O4 Front-end provides aliases

iropt

• Processes each procedure separately

• Use basic blocks

• Control flow analysis using dominators

• Parallelizer uses structural analysis

• Other optimizations using iterative algorithms

• Optimizations translate Sun-IR Sun-IR

Optimizations in iropt

• Scalar replacement of aggregates and expansion of Fortran arithmetic on complex numbers

• dependence-based analysis and transformations (O3, O4)

• linearization of array addresses• algebraic simplification and reassociation of

address expressions• loop invariant code motion• strength reduction and induction variable removal• global common-subexpression elimination• dead-code elimination

Dependence Based Analysis

• Constant propagation

• dead-code elimination

• structural control flow analysis

• loop discovery (index variables, lower and upper bounds)

• segregation of loops that have calls and early exists

• dependence analysis using GCD

• loop distribution (split loops 20)

• loop interchange

• loop fusion

• scalar replacement of array elements

• recognition of reductions

• data-cache tiling

• profitability analysis for parallel code generation

Code Generator

• First translate Sun-IR to asm+

• instruction selection

• inline of assembly language templates

• local optimizations (dead-code elimination, branch chaining, …)

• macro expansion

• data-flow analysis of live variables

• early instruction selection

• register allocation by graph coloring

• stack frame layout

• macro expansion (MAX, MIN, MOV)

• late instruction scheduling

• inline of assembly language constructs

• macro expansion

• emission of relocatable code

Optimizations on main

• Removal of unreachable code in else (except )

• Move of loop invariant “length*width”• Strength reduction of “height”• Loop unrolling by factor of four• Local variables in registers• All computations in registers• Identifying tail call• Stack frame eliminated

Missed optimizations on main

• Removal of computations

• Compute area in one instruction

• Completely unroll the loop

Optimizations on Fortran example

• Procedure integration of s1 (n=500)

• Common subexpression elimination of “a[k,j]”

• Loop unrolling

• Local variables in registers

• Software pipelining

Optimizations missed Fortran example

• Eliminating s1

• Eliminating addition in loop via linear function test replacement

POWER/PowerPC Architecture• Power

– 32 bit RISC superscalar system with– branch, integer and floating point units– optional multiprocessors (one branch)– 32 (shared) general purpose integer registers

(gr00)

– load, store, arithmetic, shift, branch, call and system control

– addresses (register+register, register+displ.)– Three address instructions

• PowerPC– Both 32 and 64 bit architecture

The IBM XL Compilers• Front-ends for PL.8, C, C++, Fortran 77, Pascal• Originated in 1983• Written in PL.8• First released for PC/RT• Generates code for Power, Intel 386, SPARC and

PowerPC • No interprocedural optimizations• (Almost) all optimizations on low level IR (XIR)

The IBM/XIL CompilerTranslator

XIL

Instruction scheduler

Register allocation

Instruction scheduler

Instruction Selection

Relocatable

Optimizer

XIL

XIL

Final assembly

XIL

TOBEY• Processes each procedure separately

• Use basic blocks

• Control flow analysis in using DFS and intervals

• YIL a higher level representation– loops– SSA form

• Data-flow analysis by interval analysis

• Iterative algorithm for non reducible

Optimizations in TOBEY

• Switches Compare|Table branch

• Mapping local variables to register+offset

• Inline for current module

• Aggressive value numbering

• global common subexpression elimination

• loop-invariant code motion

• downward store motion

• dead-store motion

• reassociation, strength reduction

• global constant propagation

• architecture specific optimizations (MAX)

• value numbering

• global common subexpression elimination

• dead code elimination

• elimination of dead induction variables

Final Assembly

• Two passes on XIL– Peephole optimizations

– Generate relocatable immage

Optimizations on main

• Removal of unreachable code in else

• Move of loop invariant “length*width”

• Strength reduction of “height”

• Loop unrolling by factor of two

• Local variables in registers

• All computations in registers

Missed optimizations on main

• Identifying tail call

• Compute area in one instruction

Optimizations on Fortran example

• n=500

• Common subexpression elimination of “a[k,j]”

• Loop unrolling 9

• Local variables in registers

• Software pipelining

Optimizations missed Fortran example

• Procedure integration of s1

• Eliminating addition in loop via linear function test replacement

Intel 386 Architecture• 32 bit CISC system

• 8 32 bit integer registers

• Support 16 and 8 bit registers

• Dedicated registers (e.g., stack frame)

• Many address modes

• Two address instructions

• 80 bits floating point

The Intel Compilers• Front-ends for C, C++, Fortran 77, Fortran 90• Front-End from Multiflow and Edison Design

Group (EDG)• Generates 386 code• Interprocedural optimization were added (1991)• Mixed optimization mode• Many optimizations based on partial redundency

elimination

The Intel CompilerFront-End

IL-1

Memory optimizer

Global optimizer

Relocatable

Interprocedural Optimizer

Code selector

Register allocation

Instruction scheduler

IL-1+IL-2

IL-1+IL-2

IL-1+IL-2

Interprocedural Optimizer

• Cross module

• Saves intermediate representations

• Interprocedural constant propagation

Memory Optimizer

• Improves memory and caches

• loop transformations

• Uses SSA form

• Data dependence

Global Optimizer

• Constant propagation

• dead code elimination

• local common subexpression elimination

• copy propagation

• partial redundency elimination

• copy propagation

• dead code elimination

Optimizations on main

• Removal of unreachable code in else

• Move of loop invariant “length*width”

• Strength reduction of “height”

• Local variables in registers

Missed optimizations on main

• Compute area in one instruction

• Identifying tail call

• Loop unrolling

Optimizations on Fortran example

• Inlinining s1 n=500

• Common subexpression elimination of “a[k,j]”

• Local variables in registers

• Linear function test replacement

Optimizations missed Fortran example

• Eliminating s1

• Loop unrolling in the inlined loop

opt Sun IBM Intel

constant

kind

dead-code (almost) loop

invariant

strength

reduction

loop-unrolling 4 2 5

register

allocation

stack-frame

eliminated

tail-call

opt Sun IBM Intel

CSE a(k, j)

integrate s1 loop-unrolling 4 2

instructions(inner-loop)

21 9 4

linear function

test replace

software pipelined

register

allocation

Future Trends in Compiler Design and Implementation

• SSA is being used more and more:– generalizes basic block optimizations to extended basic

blocks

– leads to performance improvements

• Partial redundency elimination is being used more• Partial redundency and SSA are being combined• Paralizations and vectorization are being integrated

into production compilers• Data-dependence testing, data-cache optimization

and software pipeline will advance significantly• The most active research area in scalar compilation

will be optimization

Other Trends• More and more work will be shifted from

hardware to compilers

• More advanced hardware will be available

• Higher order programming languages will be used– Memory management will be simpler– Modularity facilities– Assembly programming will hardly be used

• Dynamic (runtime) compilation will become more significant

Theoretical Techniques in CompilersTechnique Compiler Phase

Data structures All

Automata algorithms Front-End, Instruction-Selection

Graph Algorithms Control-Flow Data-Flow Register Allocation

Linear Programming Instruction Selection (Complex machines)

Diophantic Equations Parallelization

Random Algorithms