research in compilers and how it relates to software engineering part i: compiler research tomofumi...

Research in Compilers and How it Relates to Software EngineeringPart I: Compiler Research

Tomofumi Yuki

EJCP 2015June 22, Nancy

Background

Defended Ph.D. in C.S. on October 2012 Colorado State University Advisor: Dr. Sanjay Rajopadhye

Currently Inria Chargé de Recherche Rhône-Alpes, LIP @ ENS Lyon

Optimizing compiler + programming language static analysis (polyhedral model) parallel programming models High-Level Synthesis

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What is this Course About?

Research in compilers a bit about compiler itself

Understand compiler research what are the problems? what are the techniques? what are the applications?

may be do research in compilers later on!

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Be able to (partially) understand work by “compiler people” at conferences.

EJCP 2015, June 22, Nancy

What is a Compiler?

What does compiler mean to you?

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Compiler Advances

Old compiler vs recent compiler modern architecture different versions of gcc

How much speedup by compiler alone after 20 years of research?

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Compiler Advances

Old compiler vs recent compiler modern architecture different versions of gcc 2x difference after 20 years (anecdotal)

Not so much?

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Compiler Advances

Old compiler vs recent compiler modern architecture different versions of gcc 2x difference after 20 years (anecdotal)

Not so much?

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“The most remarkable accomplishment by far of the compiler field is the widespread use of high-level languages.”

by Mary Hall, David Padua, and Keshav Pingali[Compiler Research: The Next 50 Years, 2009]


Earlier Accomplishments

Getting efficient assembly register allocation instruction scheduling ...

High-level language features object-orientation dynamic types automated memory management ...

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What is Left?

Parallelism multi-cores, GPUs, ... language features for parallelism

Security/Reliability verification certified compilers

Power/Energy data movement voltage scaling

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Agenda for today

Part I: What is Compiler Research?

Part II: Compiler Optimizations

Part III: Connection to Software Engineering

Lab: Introduction to Loop Transformations

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What is a Compiler?

Bridge between “source” and “target”

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source targetcompile


Compiler vs Assembler

What are the differences?

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source targetcompile

assembly

objectassemble


Compiler vs Assembler

Compiler Many possible targets (semi-portable) Many decisions are taken

Assembler Specialized output (non-portable) Usually a “translation”

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Goals of the Compiler

Higher abstraction No more writing assemblies! enables language features

loops, functions, classes, aspects, ...

Performance while increasing productivity speed, space, energy, ... compiler optimizations

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Productivity vs Performance

Higher Abstraction ≈ Less Performance

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Performance

Abst

ract

ion

Assembly

Fortran

C

Java

Python



How much can you regain?

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Performance

Abst

ract

ion

Assembly

Fortran

C

Java

Python Python

Java

C

Fortran



How sloppy can you write code?

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Performance

Abst

ract

ion

Assembly

Fortran

C

Java

Python

Java

C

Fortran

Python


Compiler Research

Branch of Programming Languages Program Analysis, Transformations Formal Semantics Type Theory Runtime Systems Compilers ...

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Current Uses of Compiler

Optimization important for vendors many things are better left to the

compiler parallelism, energy, resiliency, ...

Code Analysis IDEs static vs dynamic analysis

New Architecture IBM Cell, GPU, Xeon-Phi, ...

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Case 1: Register Allocation

Classical optimization problem

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C = A + B;D = B + C;

load %r1, Aload %r2, Badd %r3, %r1, %r2store %r3, Cload %r1, Bload %r2, Cadd %r3, %r1, %r2store %r3, D

naïve translation

load %r1, Aload %r2, Badd %r1, %r1, %r2store %r1, Cadd %r1, %r2, %r1store %r1, D

smart compilation

3 registers8 instructions

2 registers6 instructions


Register Allocation in 5min.

Often viewed as graph coloring

Live Range: when a value is “in use” Interference: both values are “in use”

e.g., two operands of an instruction Coloring: conflicting nodes to different

reg.21

c = a + b;d = b + c;

a b c d

Live Range Analysis

a b

dc

Interference Graph

b

add %r1, %r1, %r2add %r1, %r2, %r1


Register Allocation in 5min.

Registers are limited

c = a + b;d = b + c;x = c + d;y = a + x;

a b c d x y

a = load A;c = a + b;d = b + c;x = c + d;z = load A;y = z + x;

a b c d x y z

a b

dc

yx

a b

dc

zx

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a b

dc

yx

a b

dc

zx

Live Range Splitting


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Research in Register Allocation How to do a good allocation

which variables to split which values to spill

How to do it fast? Graph-coloring is expensive Just-in-Time compilation

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“Solved”


Case 2: Instruction Scheduling Another classical problem

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X = A * B * C;Y = D * E * F;

R = A * B;X = R * C;S = D * E;Y = S * F;

naïve translation

R = A * B;S = D * E;X = R * C;Y = S * F;

smart compilation

Pipeline Stall(if mult. takes 2

cycles)Also done in

hardware(out-of-order)


DAG Scheduling + Resource Constraints

Instruction Scheduling in 5min.

X = A * B * C;Y = D * E * F;

×

A B C

×

X

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×

D E F

×

Y

Scheduling: - dependences - latency of opsResource Allocation: - #of ALUs - #of mem. requests


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Research in Instruction Scheduling Not much anymore for

speed/parallelism beaten to death hardware does it for you

Remains interesting in specific contexts faster methods for JIT energy optimization “predictable” execution

in-order cores, VLIW, etc.

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Case 1+2: Phase Ordering

Yet another classical problem practically no solution

Given optimization A and B A after B vs A before B which order is better? can you solve the problem globally?

Parallelism requires more memory trade-off: register pressure vs

parallelism

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Case 3: Bug Detection

Static Analysis to help programming

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short A = 30000;short B = 30000;short C = A + B;

Is there a problem?


Case 3: Bug Detection

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Hardware Description ≈ Assembly for HW Still in heavy use!

Case 4: High-Level Synthesis

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for (i=0; i<N; i++) for (j=i; j<N; j++) C[i] += A[i][j] * B[i];

if j<N-1 i,j+1

if j=N-1 i+1,i

i,j

× C

A

B

+


Tracks in PLDI 2015

Correctness Verification Optimization Concurrency I/II Parallelism Performance Synthesis I/II Semantics I/II Analysis Logic

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Job Market

Where do they work at? IBM Mathworks amazon start-ups

Many opportunities in France Mathworks @ Grenoble Many start-ups

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research in compilers and how it relates to software engineering part i: compiler research tomofumi...

Documents

compiler field

compiler people

compiler optimizations

compiler researchwhat

years of research

nancycompiler vs assemblerwhat

highlevel language

years anecdotalnot