In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

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 …

Tiling is a key technique for data locality optimization and is widely used in high-
performance implementations of dense matrix-matrix multiplication for multicore/manycore …

Enabling compilers to automatically optimize code has been a longstanding goal for the
compiler community. Efficiently solving this problem requires using precise cost models …

Predictive modeling using machine learning is an effective method for building compiler
heuristics, but there is a shortage of benchmarks. Typical machine learning experiments …

We propose IR2Vec, a Concise and Scalable encoding infrastructure to represent programs
as a distributed embedding in continuous space. This distributed embedding is obtained by …

In natural language processing, novel methods in deep learning, like recurrent neural
networks (RNNs) on sequences of words, have been very successful. In contrast to natural …

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 …