Architectures and Hardware for Evolutionary and Reconfigurable Computing

Call for Chapters

Nadia Nedjah, Chao Wang, Luiza de Macedo Mourelle (Eds.)

Evolutionary and reconfigurable computing methodologies have been the key techniques in computational intelligent systems, and have attracted great interest as one of the most promising architectures. The origin of evolutionary architecture and software has evolved into today's complex systems, and furthermore a variety of state-of-the-art embedded computing devices. Numerous approaches have been conducted to explore more creditable metrics beyond raw performance, such as flexibility, dependability, low-power, etc. For this book volume, we seek original contributions focusing on architectures and hardware designs that are related to evolutionary and reconfigurable computational computing systems. Chapters on architectures and hardware for evolutionary and reconfigurable computing in real-world applications are particularly welcome. The topics of interest include, but are not limited to:

Architecture framework for reconfigurable computing systems Neural chip design paradigms Evolutionary and adaptive hardware designs Adaptive network-on-chip architectures (e.g. Mesh, crossbar, etc.) FPGA and CPLD for Prototyping and real systems designs High-Level abstractions and tools for FPGAs: general-purpose and domain-specific models, languages, tools CAD techniques to facilitate the design, development, debugging, verification, and deployment of large-scale and high-performance evolutionary applications and systems Operating system software and middleware support for computational intelligent systems Design methodologies, modeling, specification, test, and verification for evolutionary and reconfigurable computational intelligent systems " Applications and design studies, accelerations for emerging applications like big data.

A tentative time schedule for this publication is as follows:

1. Manuscript submission: January 7, 2014
2. Authors Notification: April 10, 2014
3. Final version submission: June 6, 2014