HPC applications are increasingly being designed as dynamic workflows for the ease of
development and scaling. This work demonstrates how the serverless computing model can …

Serverless functions (SFs) and on-demand virtual machines (VMs) are common cloud
resources for scientific workflow applications, which are widespread in many fields. SFs are …

Serverless computing has been favored by users and infrastructure providers from various
industries, including online services and scientific computing. Users enjoy its auto-scaling …

Providing efficient Functions as a Service (FaaS) is challenging due to the serverless
programming model and highly heterogeneous and dynamic workloads. Great strides have …

In recent years, serverless computing, especially Function as a Service (FaaS), is rapidly
growing in popularity as a cloud programming model. The serverless computing model …

Serverless computing has a critical problem of function cold starts. To minimize cold starts,
state-of-the-art techniques predict function invocation times to warm them up. Warmed-up …

To explain specific phenomena, scientists perform a sequence of tasks, eg, to gather,
analyze and interpret data, forming a scientific workflow. Depending on the complexity of the …

Functions as a Service (FaaS) have gained popularity for programming public clouds due to
their simple abstraction, ease of deployment, effortless scaling and granular billing. Cloud …

Deep reinforcement learning (DRL) has gained immense success in many applications,
including gaming AI, robotics, and system scheduling. Distributed algorithms and …

Aggregated HPC resources have rigid allocation systems and programming models which
struggle to adapt to diverse and changing workloads. Consequently, HPC systems fail to …