Special Issue on Evolutionary Algorithmic Computational Techniques for VLSI Design and Many-Core Embedded Systems
• 大类 : 工程技术 - 4区
• 小类 : 计算机：硬件 - 4区
• 小类 : 计算机：理论方法 - 4区
• 小类 : 工程：电子与电气 - 4区
In the last few decades, evolutionary algorithms (EAs) have moderately established a stronghold as powerful search methods in many complex disciplines ranging from science to engineering. Even though well established as reasonable and powerful search tools, researchers in this area are now facing new challenges of increasing computational needs in today’s applications. The demand and success of EAs consist in the ease of application, majority of the concept and their ability to converge close to the global optimal design. Nevertheless, traditional EAs generally support from extremely slow convergence to locate an accurate enough solution efficiently due to the lack of individual learning potential. This often limits the practicality of EAs on many large-scale real world problems where the computational time is a determining consideration. One of the recent most important and successful areas of research that has spawned from evolutionary computations is the methodology known as memetic algorithms.
Aggressive scaling of semiconductor process technology over the last several decades has resulted in creation of many new products, such as camera, tablets, smart phones and information appliances. The trend is expected to continue for the coming years and create countless opportunities and challenges. Recent developments in semiconductor industry show a rapid increase in chip frequency and design complexity. Introduction of newer technologies is now moving towards a two year cycle as compared to traditional three year cycle. Though technology scaling helps in addressing design complexity and performance trends, it opens up a whole new spectrum of design validation challenges.
The special issue is dedicated to ascertain the prospects, progress and challenges in VLSI Design and Many core embedded systems. The topics of interest are limited to:
· Programming models, tools, languages and compilers to support energy-aware computing
· Energy-efficient memory architectures and technologies
· Architectures and design methods for real time embedded system
· Adaptive system architectures such as reconfigurable systems in hardware and software.
· FPGA implementation
· Embedded System Architectures
· Heterogeneous multi core programming
· Networking Embedded system
· Emergent computer architecture for embedded system
· Software tools and infrastructure for embedded systems