Design Space Exploration and Resource Management of Multi/Many-Core Systems
A special issue of Journal of Low Power Electronics and Applications (ISSN 2079-9268).
Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 32209
Special Issue Editors
Interests: embedded systems; MPSoC; NoC; design space exploration; run-time mapping
Special Issues, Collections and Topics in MDPI journals
Interests: interconnection network; Network-on-Chip (NoC); multi-chip system integration; wireless interconnects; data center networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The reliance of computing systems of various scales, e.g., emebbeded to cloud computing, is increasing on multi/many-core chips mainly to satisfy the high performance requirement of complex software applications. These systems are typically referred to as multi/many-core systems. At the same time, depending upon the application domain, these systems also demand energy efficiency, reliabilty and/or security. These demands can be fulfilled by exploring the design space by considering the software applications and the multi/many-core chips to find the design points leading to efficiency in all the required metrics depending upon the application domain.
Further, considering varying workloads in the systems over time, efficient resource management methodologies need to be developed to meet the requirements of performance, energy efficiency, reliability and/or security. These methodologies can perform resource management decisions online without any prior analysis or can exploit offline explore design space to take efficient run-time decisions and, thus, management.
Authors are invited to submit regular papers following the JLPEA submission guidelines, within the remit of this Special Issue call. Topics include but are not limited to:
- Design space exploration (DSE) techniques for multi/many-core systems;
- DSE considering optimisation for one or more metrics, such as accuracy, performance, energy consumption, reliability and security;
- Resource management considering various principles, e.g., machine learning and heuristics;
- Adaptive and hieracrchical resource management;
- Approximate computing to achieve trade-offs for various metrics.
Dr. Amit Kumar Singh
Dr. Amlan Ganguly
Guest Editors
Manuscript Submission Information
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Keywords
- Multicore and many-core
- Design space exploration
- Resource management
- Security
- Reliability
- Energy efficiency
- Machine learning
- Approximate computing
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