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

With the recent success of embeddings in natural language processing, research has been
conducted into applying similar methods to code analysis. Most works attempt to process the …

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 …

Accurate automatic optimization heuristics are necessary for dealing with thecomplexity and
diversity of modern hardware and software. Machine learning is aproven technique for …

The increasing complexity of computing systems places a tremendous burden on optimizing
compilers, requiring ever more accurate and aggressive optimizations. 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 …

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 …

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 …

High-level program optimizations, such as loop transformations, are critical for high
performance on multi-core targets. However, complex sequences of loop transformations …

Malware can range from simple adware to stealthy kernel control-flow modifying rootkits.
Although anti-virus software is popular, an ongoing cat-and-mouse cycle of anti-virus …