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 …
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 …
ParamILS: an automatic algorithm configuration framework
The identification of performance-optimizing parameter settings is an important part of the
development and application of algorithms. We describe an automatic framework for this …
development and application of algorithms. We describe an automatic framework for this …
Scalable gaussian process-based transfer surrogates for hyperparameter optimization
Algorithm selection as well as hyperparameter optimization are tedious task that have to be
dealt with when applying machine learning to real-world problems. Sequential model-based …
dealt with when applying machine learning to real-world problems. Sequential model-based …
Rapidly selecting good compiler optimizations using performance counters
Applying the right compiler optimizations to a particular program can have a significant
impact on program performance. Due to the non-linear interaction of compiler optimizations …
impact on program performance. Due to the non-linear interaction of compiler optimizations …
Automatic feature generation for machine learning--based optimising compilation
Recent work has shown that machine learning can automate and in some cases outperform
handcrafted compiler optimisations. Central to such an approach is that machine learning …
handcrafted compiler optimisations. Central to such an approach is that machine learning …
Mitigating the compiler optimization phase-ordering problem using machine learning
S Kulkarni, J Cavazos - … of the ACM international conference on Object …, 2012 - dl.acm.org
Today's compilers have a plethora of optimizations to choose from, and the correct choice of
optimizations can have a significant impact on the performance of the code being optimized …
optimizations can have a significant impact on the performance of the code being optimized …
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 …
Machine learning in compilers: Past, present and future
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 …
compiler is huge and the systems on which they run are complex, heterogeneous, non …
[图书][B] The compiler design handbook: optimizations and machine code generation
YN Srikant, P Shankar - 2002 - taylorfrancis.com
The widespread use of object-oriented languages and Internet security concerns are just the
beginning. Add embedded systems, multiple memory banks, highly pipelined units …
beginning. Add embedded systems, multiple memory banks, highly pipelined units …