Distributed cloud/edge (DCE) platform has become popular in recent years. This paper
proposes a new AI benchmark suite for assessing the performance of DCE platforms in …

Almost ten years after its premises, the Grid'5000 platform has become one of the most
complete testbeds for designing or evaluating large-scale distributed systems. Initially …

AI accelerator is a specialized hardware processing unit that provides high throughput,
lower latency, and higher energy efficiency compared to existing server-based processors …

As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …

Due to the popularity of the FaaS programming model, there is now a wide variety of
commercial and open-source FaaS systems. Hence, for comparison of different FaaS …

Nowadays, deep neural networks (DNNs) are the core enablers for many emerging edge AI
applications. Conventional approaches for training DNNs are generally implemented at …

Building large AI fleets to support the rapidly growing DL workloads is an active research
topic for modern cloud providers. Generating accurate benchmarks plays an essential role in …

Extensive deployment of AI services, especially mobile AI, requires the support of edge
computing. This support is not just at the network architecture level, the design, adaptation …

Abstract Infrastructure-as-a-Service (IaaS) cloud computing is an emerging commercial
infrastructure paradigm under which clients (users) can lease resources when and for how …

Distributed cloud/edge resources are needed to execute pervasive artificial intelligence
tasks, collectively. The AI workload and data sets have variable multitasking granularity …