The emergence of ML in various cloud system management tasks (eg, workload autoscaling
and job scheduling) has become a core driver of ML-centric cloud platforms. However, there …

Serverless Function-as-a-Service (FaaS) is an emerging cloud computing paradigm that
frees application developers from infrastructure management tasks such as resource …

Serverless Function-as-a-Service (FaaS) offers improved programmability for customers, yet
it is not server-" less" and comes at the cost of more complex infrastructure management (eg …

Abstract Function-as-service (FaaS) platforms promise a simpler programming model for
cloud computing, given that providers take care of the overall resource management while …

Foundation models (FMs) are machine learning models that are trained broadly on large-
scale data and can be adapted to a set of downstream tasks via fine-tuning, few-shot …

Energy efficiency is pressing in today's cloud datacenters. Various power management
strategies, such as oversubscription, power capping, and dynamic voltage and frequency …

Serverless computing has reshaped the cloud computing landscape by offering benefits
such as auto-scalability, streamlined operational management, and granular billing. As its …

Writing thread safe code for concurrent processing requires experience and training, thus
legacy research code are usually single threaded, which post a challenge when it comes to …

This paper explores resource allocation in serverless cloud computing platforms and
proposes an optimization approach for autoscaling systems. Serverless computing relieves …

Serverless computing has gained widespread popularity due to its ability to dynamically
allocate resources and abstract away the underlying infrastructure, allowing developers to …