2017 Workshop on Exploiting Accelerator Diversity for Cognitive Workloads

Cognitive computing is transforming the way we perceive the world. Today, applications of cognitive computing rely on machine learning models that are trained in the cloud and inference requests are made in real-time using end-user edge devices. This, thus far, has largely been the way that cognitive services are deployed. However, concerns over security, privacy, network connectivity etc. are sparking a paradigm shift in cognitive computing. Interest is rapidly growing in deploying training and inference engines at the edge, which in and of itself is evolving at an astounding pace. Bringing cognitive computing to the edge devices opens up several new opportunities and challenges for researchers. Edge devices are short on resources, such as power, networking, storage, compute etc.

Therefore, cognitive edge computing requires us to understand the issues and discover novel solutions. The workshop is meant to foster an interactive discussion about emerging application domains and the role of cognitive computing in these new domains. In addition, the workshop is meant to lead to new discussions and insights on cognitive algorithms, architectures and system-level design.