A survey on compiler autotuning using machine learning
Since the mid-1990s, researchers have been trying to use machine-learning-based
approaches to solve a number of different compiler optimization problems. These …
approaches to solve a number of different compiler optimization problems. These …
Methodological principles for reproducible performance evaluation in cloud computing
The rapid adoption and the diversification of cloud computing technology exacerbate the
importance of a sound experimental methodology for this domain. This work investigates …
importance of a sound experimental methodology for this domain. This work investigates …
Machine learning in compiler optimization
In the last decade, machine-learning-based compilation has moved from an obscure
research niche to a mainstream activity. In this paper, we describe the relationship between …
research niche to a mainstream activity. In this paper, we describe the relationship between …
Milepost gcc: Machine learning enabled self-tuning compiler
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …
A large-scale study of the impact of feature selection techniques on defect classification models
The performance of a defect classification model depends on the features that are used to
train it. Feature redundancy, correlation, and irrelevance can hinder the performance of a …
train it. Feature redundancy, correlation, and irrelevance can hinder the performance of a …
Efficient compiler autotuning via bayesian optimization
A typical compiler such as GCC supports hundreds of optimizations controlled by
compilation flags for improving the runtime performance of the compiled program. Due to the …
compilation flags for improving the runtime performance of the compiled program. Due to the …
Mapping parallelism to multi-cores: a machine learning based approach
Z Wang, MFP O'Boyle - Proceedings of the 14th ACM SIGPLAN …, 2009 - dl.acm.org
The efficient mapping of program parallelism to multi-core processors is highly dependent
on the underlying architecture. This paper proposes a portable and automatic compiler …
on the underlying architecture. This paper proposes a portable and automatic compiler …
Cgptuner: a contextual gaussian process bandit approach for the automatic tuning of it configurations under varying workload conditions
S Cereda, S Valladares, P Cremonesi… - Proceedings of the VLDB …, 2021 - dl.acm.org
Properly selecting the configuration of a database management system (DBMS) is essential
to increase performance and reduce costs. However, the task is astonishingly tricky due to a …
to increase performance and reduce costs. However, the task is astonishingly tricky due to a …
Micomp: Mitigating the compiler phase-ordering problem using optimization sub-sequences and machine learning
Recent compilers offer a vast number of multilayered optimizations targeting different code
segments of an application. Choosing among these optimizations can significantly impact …
segments of an application. Choosing among these optimizations can significantly impact …
Cole: compiler optimization level exploration
K Hoste, L Eeckhout - Proceedings of the 6th annual IEEE/ACM …, 2008 - dl.acm.org
Modern compilers implement a large number of optimizations which all interact in complex
ways, and which all have a different impact on code quality, compilation time, code size …
ways, and which all have a different impact on code quality, compilation time, code size …