Since the mid-1990s, researchers have been trying to use machine-learning-based
approaches to solve a number of different compiler optimization problems. These …

Despite recent increase in research on improvement of non-functional properties of
software, such as energy usage or program size, there is a lack of standard benchmarks for …

Interest in applying Artificial Intelligence (AI) techniques to compiler optimizations is
increasing rapidly, but compiler research has a high entry barrier. Unlike in other domains …

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 …

Recent compilers offer a vast number of multilayered optimizations targeting different code
segments of an application. Choosing among these optimizations can significantly impact …

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 …

To ensure compilers' quality, compiler testing has received more and more attention, and
test-program generation is the core task. In recent years, some approaches have been …

Reinforcement learning (RL) is emerging as a powerful technique for solving complex code
optimization tasks with an ample search space. While promising, existing solutions require a …

Compilers are a kind of important software, and similar to the quality assurance of other
software, compiler testing is one of the most widely-used ways of guaranteeing their quality …

A predictive compiler uses properties of a program to decide how to optimize it. The compiler
is trained on a collection of programs to derive a model which determines its actions in face …