The ever-increasing global demand for computing power and improved performance drives the embedded systems towards multi-core systems. This is because of the reason that multi-core and many-core systems are formulating itself as a most significant choice of the solution across the electronics and communication sectors. However, its implementations are still at infancy and posses numerous research gaps. Some of the most critical challenges include risk associated with migrating legacy software to work with multi-core systems; what are the better technologies that can be used? Will the incorporation of virtual techniques can enhance the performance? Will it be cost-efficient and reliable?. Finding the answer to these questions can probably help the research community leverage the most powerful high-performance multi-core solutions that extensively offer advanced tools and techniques.
Presently, computing networks are moving towards a new era of digital computing. However, the progress towards global network connectivity increases the need for higher computing power and makes the existing solutions to be inappropriate. Already, the high-end system applications such as networking and wireless infrastructure platforms have started to adopt multi-core and many-core solutions. As a matter of fact, it is often impossible for a single-threaded performance to offer consistent services without the integration of geometrically increasing power. This instance can potentially increase the system cost with reduced reliability measures. Thus, in order to retain the power at a controllable level, it has become a necessity for today’s applications to go for multi-core and many-core systems as an alternative to continually increasing frequency rate. Recent multi-core and many-core processors offer various levels of parallelism via numerous range of architectures for data-parallel execution. Hence, implementing multi-level parallelism has become a critical requirement for the current and future processors to cope with increasing demand. In this context, this special issue aims to bring-out the advances in multi-core and many-core systems for future generation computing systems. It offers a forum for researchers and industrial professionals to share their novel and innovative ideas against this background.
The topics of interest include, but not limited to, the following:
Advances in multi-core and many-core design, architectures, and programming models
Energy-efficient design protocols for multi-core and may-core systems
Low power design for multi-core and many-core systems
Advances in interconnection network infrastructures for multi-core and many-core systems
Programming models, tools, and languages to support energy-aware multi-core and many-core computing
Advances in system security for multi-core and many-core architectures
Modern multi-core and many-core architectures
Advanced network interface designs for Intra/inter-chip communication
On-chip network architectures and deployment models for multi-core and many-core systems
Advanced communication modeling and benchmarking technologies for multi-core and many-core approaches
Emerging interconnect technologies for multi-core and many-core systems
Submission Deadline (Full-Paper): May 1, 2021
Acceptance Deadline: Jan 10, 2022
Dr. VICENTE GARCÍA DÍAZ
University of Oviedo, Spain.
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Dr. Vicente Garcia Diaz is working as an Associate Professor in the Computer Science Department of the University of Oviedo. He obtained his PhD from the University of Oviedo in Computer Engineering. He completed his graduation in Prevention of Occupational Risks and he is a Certified Associate in Project Management through the Project Management Institute. His teaching interests are primarily in the design and analysis of algorithm. He worked as a visiting professor at universities and centers in different countries. His research interests include model-driven engineering, domain specific languages, technology for learning and entertainment, project risk management, software development processes and practices.
Dr. JERRY CHUN-WEI LIN
Western Norway University of Applied Sciences,
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Dr. Jerry Chun-Wei Lin, is working as a Professor at the Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. He worked as an Assistant Professor (2012/10 – 2016/12) and Associate Professor (2016/12 – 2018/07) at School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, China. He has been awarded as the Most Cited Chinese Researcher in 2018 and 2019 in Elsevier. He is the member of IET and senior member of IEEE and ACM. He is the project leader of SPMF and PPSF projects. His research interests include Data mining, Soft Computing, Artificial Intelligence, Privacy-preserving, Optimization and Security Technologies.
Dr. JUAN ANTONIO MORENTE MOLINERA
PDI, University of Granada.
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Dr. Juan Antonio Morente Molinera, is working as a Professor at the Department of Engineering, School of Engineering and Technology, Universidad International de la Rioja, Logrono, Spain. He obtained his PhD in Information and Communication Technology with a National Research Training Grant from the University of Granada, Spain in 2015.He is part of the Soft Computing and Intelligent Information systems and Mobility and User Experience Research Groups at the University of Granada and UNIR. His research interests include Artificial Intelligence, Fuzzy set theory, Maxwell equations, Bio Informatics, Decision Support System, Knowledge Management, Linguistics, Molecular Biophysics.
Dr. THILO PIONTECK
Otto-von-Guericke University Magdeburg
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The chair Hardware-Oriented Technical Computer Science researches new architectural concepts for the realization of runtime-adaptive, performance- and energy efficient digital systems. Both dedicated hardware accelerators in the basis of dynamical reconfigurable FPGAs and combined hardware/software systems are considered. Applications from embedded systems and high performance computing are of interest, since their contradicting requirements on energy efficiency, flexibility, performance, and size prohibit a realization with traditional hardware- and software solutions. Of special interest are database systems, sensor fusion in medical context, and electronic image correction.