Clustering-Based Selection for the Exploration of Compiler Optimization Sequences

Luiz G. A. Martins, Ricardo Nobre, João M. P. Cardoso, Alexandre C. B. Delbem, Eduardo Marques

ACM Transactions on Architecture and Code Optimization 2016 article cited by 70

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importance 4/10 ai assisted Embedded Systems Design Techniques compiler software stage: research

Problem

Exhaustively exploring all viable compiler optimization sequences is infeasible, yet pass ordering strongly impacts performance and depends on platform and application.

Why it matters

Compiler optimization sequences directly determine software performance, and manual exploration is too complex and time-consuming.

What the AI did

A clustering-based design space exploration scheme groups similar functions and explores a reduced search space built from optimizations previously suggested for functions in each cluster.

Results

not stated in source

Impact

Abstract claims the scheme selects optimization sequences to improve per-function performance and reduce exploration time.

Record

Venue	ACM Transactions on Architecture and Code Optimization
Published	2016
Work type	article
Authors	Luiz G. A. Martins, Ricardo Nobre, João M. P. Cardoso, Alexandre C. B. Delbem, Eduardo Marques
Citations	70 (OpenAlex, at import time)
References	38
Model or method	clustering-based DSE scheme
Organization	not stated in source
Primary source	https://doi.org/10.1145/2883614
Open access	bronze
Keywords	compiler optimization, design space exploration, clustering, phase ordering, code performance

Importance rating

4 / 10

real but narrower advance

Compiler pass ordering strongly impacts software performance and exhaustive exploration is infeasible; a real but narrower computing advance, with no stated scale of affected users or industry.

Basis: inferred. Judged from the source text, which gives no explicit scale. Stated scale: not stated in source. Method and limits.

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