Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart
Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data …

DNN/Accelerator co-design has shown great potential in improving QoR and performance.
Typical approaches separate the design flow into two-stage:(1) designing an application …

Edge AI is transforming the way computers interact with the real world, allowing IoT devices
to make decisions using the 99% of sensor data that was previously discarded due to cost …

Domain-specific designs offer greater energy efficiency and performance gain than general-
purpose processors. For this reason, modern system-on-chips have a significant portion of …

IoT systems are used for performing a variety of essential tasks in wide-ranging sectors,
such as healthcare, smart cities, agriculture, and industrial automation. Most of these …

DNN accelerators are often developed and evaluated in isolation without considering the
cross-stack, system-level effects in real-world environments. This makes it difficult to …

Specialized hardware has become an indispensable component to deep neural network
(DNN) acceleration. To keep up with the rapid evolution of neural networks, holistic and …

Recently, automated co-design of machine learning (ML) models and accelerator
architectures has attracted significant attention from both the industry and academia …

In recent years, Artificial Intelligence (AI) has been widely deployed in a variety of business
sectors and industries, yielding numbers of revolutionary applications and services that are …

In promising edge systems, AI algorithms and their hardware implementations are often joint
optimized as integrated solutions to solve end-to-end design problems. Joint optimization …