A survey on compiler autotuning using machine learning

AH Ashouri, W Killian, J Cavazos, G Palermo… - ACM Computing …, 2018 - dl.acm.org
Since the mid-1990s, researchers have been trying to use machine-learning-based
approaches to solve a number of different compiler optimization problems. These …

Efficient compiler autotuning via bayesian optimization

J Chen, N Xu, P Chen, H Zhang - 2021 IEEE/ACM 43rd …, 2021 - ieeexplore.ieee.org
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 …

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 …

Micomp: Mitigating the compiler phase-ordering problem using optimization sub-sequences and machine learning

AH Ashouri, A Bignoli, G Palermo, C Silvano… - ACM Transactions on …, 2017 - dl.acm.org
Recent compilers offer a vast number of multilayered optimizations targeting different code
segments of an application. Choosing among these optimizations can significantly impact …

Cobayn: Compiler autotuning framework using bayesian networks

AH Ashouri, G Mariani, G Palermo, E Park… - ACM Transactions on …, 2016 - dl.acm.org
The variety of today's architectures forces programmers to spend a great deal of time porting
and tuning application codes across different platforms. Compilers themselves need …

Machine learning in compilers: Past, present and future

H Leather, C Cummins - 2020 Forum for Specification and …, 2020 - ieeexplore.ieee.org
Writing optimising compilers is difficult. The range of programs that may be presented to the
compiler is huge and the systems on which they run are complex, heterogeneous, non …

Clustering-based selection for the exploration of compiler optimization sequences

LGA Martins, R Nobre, JMP Cardoso… - ACM Transactions on …, 2016 - dl.acm.org
A large number of compiler optimizations are nowadays available to users. These
optimizations interact with each other and with the input code in several and complex ways …

A graph-based iterative compiler pass selection and phase ordering approach

R Nobre, LGA Martins, JMP Cardoso - ACM SIGPLAN Notices, 2016 - dl.acm.org
Nowadays compilers include tens or hundreds of optimization passes, which makes it
difficult to find sequences of optimizations that achieve compiled code more optimized than …

Reinforcement learning strategies for compiler optimization in high level synthesis

H Shahzad, A Sanaullah, S Arora… - 2022 IEEE/ACM …, 2022 - ieeexplore.ieee.org
High Level Synthesis (HLS) offers a possible programmability solution for FPGAs by
automatically compiling CPU codes to custom hardware configurations, but currently …

Predictive modeling methodology for compiler phase-ordering

AH Ashouri, A Bignoli, G Palermo… - Proceedings of the 7th …, 2016 - dl.acm.org
Today's compilers offer a huge number of transformation options to choose among and this
choice can significantly impact on the performance of the code being optimized. Not only the …