The threat posed by wildfires or bushfires has become a severe global issue due to the
increase in human activities in forested areas and the impact of climate change …

Since emerging edge applications such as Internet of Things (IoT) analytics and augmented
reality have tight latency constraints, hardware AI accelerators have been recently proposed …

This paper describes Acies-OS, a content-centric platform for edge AI twinning and
orchestration that allows easy deployment, re-configuration, and control of edge AI services …

Background: Given the fast-paced nature of today's technology, which has surpassed
human performance in tasks like image classification, visual reasoning, and English …

Model-serving systems expose machine learning (ML) models to applications
programmatically via a high-level API. Cloud platforms use these systems to mask the …

Automated machine learning (AutoML) greatly eases human efforts in architecture
engineering. However, mainstream AutoML methods like neural architecture search (NAS) …

The growing popularity of machine learning algorithms and the wide availability of hardware
accelerators have brought up new challenges on inference serving. This paper explores the …

Traditionally, multi-tenant cloud and edge platforms use fair-share schedulers to fairly
multiplex resources across applications. These schedulers ensure applications receive …