The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, 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 …

Over the last years Transactional Memory (TM) gained growing popularity as a simpler,
attractive alternative to classic lock-based synchronization schemes. Recently, the TM …

Transactional Memory was recently integrated in Intel processors under the name TSX. We
show that its performance can be significantly affected by the configuration of its interplay …

In this paper we investigate the issue of automatically identifying the “natural” degree of
parallelism of an application using software transactional memory (STM), ie, the workload …

Transactional Memory (TM) is a practical programming paradigm for developing concurrent
applications. Performance is a critical factor for TM implementations, and various studies …

Context: The software development industry is rapidly adopting machine learning for
transitioning modern day software systems towards highly intelligent and self-learning …

The Transactional Memory (TM) paradigm promises to greatly simplify the development of
concurrent applications. This led, over the years, to the creation of a plethora of TM …

In this article we exploit a combination of analytical and Machine Learning (ML) techniques
in order to build a performance model allowing to dynamically tune the level of concurrency …

Transactional Memory (TM) is a programmer friendly alternative to traditional lock-based
concurrency. Although it intends to simplify concurrent programming, the performance of the …