We propose a set of optimization techniques for transforming a generic AI codebase so that
it can be successfully deployed to a restricted serverless environment, without compromising …

Deployed AI platforms typically ship with bulky system architectures which present
bottlenecks and a high risk of failure. A serverless deployment can mitigate these factors and …

Serverless platforms facilitate transparent resource elasticity and fine-grained billing, making
them an attractive choice for data analytics. We find that while server-centric analytics …

The appeal of serverless (FaaS) has triggered a growing interest on how to use it in data-
intensive applications such as ETL, query processing, or machine learning (ML). Several …

Serverless computing has emerged as a new paradigm for running short-lived computations
in the cloud. Due to its ability to handle IoT workloads, there has been considerable interest …

Emerging IoT applications with real-time latency constraints require new data processing
systems operating at the Edge. Serverless computing offers a new compelling paradigm …

Resource allocation for serverless query processing is a challenge. Unfortunately, prior
approaches have treated queries as black boxes, thereby missing significant resource …

Serverless computing is an emerging cloud deployment model where developers can
concentrate on developing application logic without worrying about the underlying …

The conference papers and full proceedings are available to registered attendees now and
will be available to everyone beginning Wednesday, July 14, 2021. Paper abstracts and …

Many emerging novel applications expect" near real-time" processing and responses, which
can not be guaranteed by today's Cloud and would require processing at the Edge …