An evident challenge ahead for the integrated circuit (IC) industry is the investigation and
development of methods to reduce the design complexity ensuing from growing process …

Computing systems have undergone a tremendous change in the last few decades with
several inflexion points. While Moore's law guided the semiconductor industry to cram more …

Neural Network (NN) accelerators are currently widely deployed in various security-crucial
scenarios, including image recognition, natural language processing and autonomous …

This paper introduces PRIMAL, a novel learning-based framework that enables fast and
accurate power estimation for ASIC designs. PRIMAL trains machine learning (ML) models …

Block partition structure has been recognized as a crucial module in video coding scheme.
Recently, a quadtree plus binary tree (QTBT) block partition structure has been proposed in …

In this work, we evaluate bi-directional and unidirectional FPGA routing architectures in
terms of energy and power consumption using an updated power estimation framework …

We present the first application of field programmable gate arrays (FPGAs) as new,
customizable hardware architectures for carrying out fast and energy-efficient quantum …

In this paper, a new and efficient methodology is proposed to quickly and precisely evaluate
the power consumption and performance of wireless communication base-band systems …

Architecture reverse engineering has become an emerging attack against deep neural
network (DNN) implementations. Several prior works have utilized side-channel leakage to …

The efficiency of power optimization tools depends on information on design power provided
by the power estimation models. Power models targeting different power groups can enable …