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

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 …

Optimizations are the fundamental component of compilers. Bugs in optimizations have
significant impacts, and can cause unintended application behavior and disasters …

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 …

The phase-ordering problem of modern compilers has received a lot of attention from the
research community over the years, yet remains largely unsolved. Various optimization …

The ever increasing memory requirements of several applications has led to increased
demands which might not be met by embedded devices. Constraining the usage of memory …

Optimization sequences are often employed in compilers to improve the performance of
programs, but may trigger critical compiler bugs, eg, compiler crashes. Although many …

Compiler bugs may be triggered when programs are optimized with optimization sequences.
However, diagnosing compiler optimization sequence bugs is difficult due to limited …

For the past 25 years, we have witnessed an extensive application of Machine Learning to
the Compiler space; the selection and the phase-ordering problem. However, limited works …

This paper presents the interesting observation that by performing fewer of the optimizations
available in a standard compiler optimization level such as-02, while preserving their …