UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Mitigating the Compiler Optimization Phase-Ordering

Problem using Machine Learning

Sameer KulkarniJohn Cavazos

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

• Introduction to Phase Ordering

• Present State-of-the-Art• Proposed Solution

• Understand code• Predict optimization

• An example• Results• Questions

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

What is Phase Ordering? Change ordering of a given set

optimizationsOpt. 1

Opt. 2

Opt. 3

Opt. 4

Opt. 1

Opt. 3

Opt. 2

Opt. 4

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Why is it important? Plethora of optimizations to

choose. All interact with each other

Register Allocation & Instruction Scheduling

Loop Unrolling & CSE Branch Optimization & Static

Analysis

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

• Introduction to Phase Ordering

• Present State-of-the-Art• Proposed Solution

• Understand code• Predict optimization

• An example• Results• Questions

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Present Solutions Developer’s intuition Using a static sequence using

search Pseudo Random Search (ML)

Hill Climbing, Genetic Algorithm

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Generation 1

Generation 2

Using Genetic Algorithms…

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Disadvantages of State-of-art One size fits all approach

Change in Compiler Change in Architecture Change in Code

Expensive Search

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

A simple experiment Select a set of optimizations, and

set a sequence length Generate 500 random sequences Use each of the optimization

sequence to compile and run a set of benchmarks

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

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1.05

1.1

1.15

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1.25Effects of static vs dynamic sequence

Best overall Sequence Best Sequence per benchmark

Spee

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SPECjvm 98 Grande

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

• Introduction to Phase Ordering

• Present State-of-the-Art• Proposed Solution

• Understand code• Predict optimization

• An example• Results• Questions

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Proposed Solution

Analyze Code

Predict best

optimization

End optimizati

ons?

Apply Optimizati

on

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Static Source Code Features Method level

information Instruction

Mix conditionals memory ops size locals space

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Static Source Code Features Method level

information Instruction

Mix conditionals memory ops size locals space

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Proposed Solution

Analyze Code

Predict best

optimization

End optimizati

ons?

Apply Optimizati

on

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Neural Network

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Proposed Solution

Analyze Code

Predict best

optimization

End optimizatio

ns?

Apply Optimizatio

n

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Neuro Evolution of Augmented Topologies Evolutionary approach to ANNs Starts with a minimally connected

network

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Generation 1 Generation nGeneration 2

Using NEAT…

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

• Introduction to Phase Ordering

• Present State-of-the-Art• Proposed Solution

• Understand code• Predict optimization

• An example• Results• Questions

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

scimark.lu bencmark

Generated by default O3

Generated by NEAT

UNIVERSITY OF DELAWARE • Computer & Information Sciences Department

Advantages Source code agnostic

Customized optimization sequence Train once, use every-time

Elegant stopping criteria Optimization sequence length is not

static Saves time by intelligent selection

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

• Introduction to Phase Ordering

• Present State-of-the-Art• Proposed Solution

• Understand code• Predict optimization

• An example• Results• Questions

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

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UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Results on SpecJVM98Sp

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3

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Results on SpecJVM2008Sp

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3

UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Results on DaCapoSp

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UNIVERSITY OF DELAWARE • COMPUTER & INFORMATION SCIENCES DEPARTMENT

Mitigating the Compiler Optimization Phase-Ordering

Problem using Machine Learning

Thank you!