ACM Transactions on Design Automation of Electronic Systems

Driven by Moore’s law, the chip design complexity is steadily increasing. Electronic Design Automation (EDA) has been able to cope with the challenging very large-scale integration process, assuring scalability, reliability, and proper time-to-market. ...

Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years, this use has exponentially increased due to the advancement of high-...

The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which ...

Low-power analog design is a hot topic for various power efficient applications. Sizing low-power analog circuits is not easy because the increasing uncertainties from low-voltage techniques magnify process variation effects on the design yield. ...

Analog IC performance has a strong dependence on interconnect RC parasitics, which are significantly affected by wire sizes in recent technologies, where minimum-width wires have high resistance. However, performance-driven wire sizing for analog ICs has ...

Designing high-performance adders and multiplier components for diverse specifications and constraints is of practical concern. However, selecting the best architecture for adder or multiplier, which largely affects the performance of synthesized circuits,...

Chip floorplanning has long been a critical task with high computation complexity in the physical implementation of VLSI chips. Its key objective is to determine the initial locations of large chip modules with minimized wirelength while adhering to the ...

Submitted to the Special Issue on Machine Learning for CAD (ML-CAD). Competitive strength in semiconductor field depends on yield. The challenges associated with designing and manufacturing of leading-edge integrated circuits (ICs) have increased that ...

Predicting workload behavior during workload execution is essential for dynamic resource optimization in multi-processor systems. Recent studies have proposed advanced machine learning techniques for dynamic workload prediction. Workload prediction can be ...

Field-programmable gate arrays (FPGAs) have grown to be an important platform for integrated circuit design and hardware emulation. However, with the dramatic increase in design scale, it has become a key challenge to partition very large scale ...

High-level Synthesis (HLS) Design-Space Exploration (DSE) aims at identifying Pareto-optimal synthesis configurations whose exhaustive search is unfeasible due to the design-space dimensionality and the prohibitive computational cost of the synthesis ...

Supervised machine learning requires large amounts of labeled data for training. In power, performance, and area (PPA) estimation of embedded memories, every new memory compiler version is considered independently of previous compiler versions. Since the ...

One of the greatest challenges in integrated circuit design is the repeated executions of computationally expensive SPICE simulations, particularly when highly complex chip testing/verification is involved. Recently, pseudo-transient analysis (PTA) has ...

Due to the globalization of Integrated Circuit supply chain, hardware Trojans and the attacks that can trigger them have become an important security issue. One type of hardware Trojans leverages the “don’t care transitions” in Finite-state Machines (FSMs)...

Continuous-flow microfluidic biochips have emerged as a potential low-cost and fast-responsive lab-on-chip platform. They have attracted much attention due to their capability of performing various biochemical applications concurrently and automatically ...