The rapid advancements and stringent requirements of modern embedded computing
systems have led to a surge in the demand for customized processors that can efficiently …

High-level synthesis (HLS) aims to raise the abstraction layer in hardware design, enabling
the design of domain-specific accelerators (DSAs) like field-programmable gate arrays …

Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in
learning and predicting on large-scale data present in social networks, biology, etc. Since …

Despite the great advance achieved by electronic design automation (EDA) tools, there is
still a long way towards hardware agile development, whose ultimate goal is to reduce chip …

The efficient and timely optimization of microarchitecture for a target application is hindered
by the long evaluation runtime of a design candidate, creating a serious burden. To tackle …

There are plenty of graph neural network (GNN) accelerators being proposed. However,
they highly rely on users' hardware expertise and are usually optimized for one specific GNN …

There have been several recent works proposed to utilize model-based optimization
methods to improve the productivity of using high-level synthesis (HLS) to design domain …

Most system optimization techniques focus on finding the values of the system components
to achieve the best performance. Searching over all component values gives the search …

High-level synthesis, source-to-source compilers, and various Design Space Exploration
techniques for pragma insertion have significantly improved the Quality of Results of …

Extensible processors, which combine programmability and efficiency, are emerging as a
promising approach in the field of embedded computing. Automated synthesis of custom …