The wave of modernization around us has put the automotive industry on the brink of a
paradigm shift. Leveraging the ever-evolving technologies, vehicles are steadily …

Global warming is one of the most compelling environmental threats today, as the rise in
energy consumption and CO2 emission caused a dreadful impact on our environment. The …

The growing energy and performance costs of deep learning have driven the community to
reduce the size of neural networks by selectively pruning components. Similarly to their …

Domain-specific hardware is becoming a promising topic in the backdrop of improvement
slow down for general-purpose processors due to the foreseeable end of Moore's Law …

With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …

As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep
Neural Networks (DNNs) have quickly attracted widespread attention. However, it is …

Edge intelligence (EI) is becoming one of the research hotspots among researchers, which
is believed to help empower intelligent transportation systems (ITS). ITS generates a large …

Given recent algorithm, software, and hardware innovation, computing has enabled a
plethora of new applications. As computing becomes increasingly ubiquitous, however, so …

Package-level integration using multi-chip-modules (MCMs) is a promising approach for
building large-scale systems. Compared to a large monolithic die, an MCM combines many …

This paper presents Timeloop, an infrastructure for evaluating and exploring the architecture
design space of deep neural network (DNN) accelerators. Timeloop uses a concise and …