Recently, both industry and academia have proposed several different neuromorphic
systems to execute machine learning applications that are designed using Spiking Neural …

Ever increasing embedded system design complexity combined with a very tight time-to-
market window has revolutionized the embedded-system design process. The concurrent …

Modern microprocessors such as Intel's Pentium chip typically contain many millions of
transistors. They are known generically as Very Large-Scale Integrated (VLSI) systems, and …

System-Level Design Techniques for Energy-Efficient Embedded Systems addresses the
development and validation of co-synthesis techniques that allow an effective design of …

Computational chemistry is the leading application to demonstrate the advantage of
quantum computing in the near term. However, large-scale simulation of chemical systems …

In this paper, we concentrate on aspects related to the synthesis of distributed embedded
systems consisting of programmable processors and application-specific hardware …

This paper describes lessons we have learned over the past several years about teaching
the design of modern embedded computing systems. An embedded computing system uses …

Temperature affects not only the performance but also the power, reliability, and cost of the
embedded system. This paper proposes a temperature-aware task allocation and …

As technology scales, transient faults have emerged as a key challenge for reliable
embedded system design. This paper proposes a design methodology that incorporates …

This paper introduces an allocation and scheduling algorithm that efficiently handles
conditional execution in multi-rate embedded system. Control dependencies are introduced …