IEEE Transactions on Sustainable Computing

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From the October-December 2017 issue

Adaptive Multi-Voltage Scaling with Utilization Prediction for Energy-Efficient Wireless NoC

By Hemanta Kumar Mondal, Sri Harsha Gade, Shashwat Kaushik, and Sujay Deb

Featured article thumbnail image Networks-on-Chip (NoCs) are fast becoming the de-facto communication infrastructures in chip multi-processors for large-scale applications. Wireless NoCs (WNoCs) offer a promising solution to reduce the long-distance communication bottlenecks of conventional NoCs by augmenting them with single hop, long-range wireless links. However, power consumption in routers and network elements still remains considerably high at ultra-deep submicron technologies. Analysis of network resources for several benchmarks shows that, utilization is application dependent and the desired performance can be achieved even without operating all resources at maximum specifications. In this work, we propose an energy-efficient WNoC architecture using Adaptive Multi-Voltage Scaling (AMS) to dynamically vary supply voltage for NoC routers and Wireless Interfaces (WIs) without adversely impacting performance. The proposed scheme uses a probabilistic model to predict router utilization during different application phases and scales voltage accordingly. It further reduces network energy by power-gating WIs that are not engaged in active communication to minimize their power consumption. We present detailed utilization estimation procedure, AMS control mechanism, and its hardware implementation. It saves up to 56 percent in network packet energy consumption and 62.50 percent power consumption in WIs for 256 core system as compared to baseline architectures without incurring significant performance penalty and area overheads.

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Editorials and Announcements

Announcements

  • Congratulations to Albert Zomaya on his appointment as 2016-2018 Editor-in-Chief of IEEE Transactions on Sustainable Computing. Dr. Zomaya is currently the Chair Professor of High Performance Computing & Networking and Director of the Centre for Distributed and High Performance Computing in the School of Information Technologies, The University of Sydney.

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Call for Papers

Special Issue on Beyond the Energy & Performance Scaling Boundaries of Modern Computer Architectures

Submission deadline: February 21, 2018. View PDF.

State-of-the-art microprocessor and memory chips are conservatively manufactured and operate at pessimistic levels of supply voltage, clock frequency and DRAM refresh rate for addressing the worsening static and dynamic variability in nanometer technologies. Typically, the worst chips being in the weakest corners of the manufacturing process determine the nominal values of the operating conditions although it is widely known that a very large number of chips can safely operate at reduced voltage levels, increased frequencies and relaxed DRAM refresh rates. The margins between the nominal values of the parameters and the actual safe values of individual chips can potentially lead to large savings in energy/power consumption or to large improvements of the performance. Fine-grained tuning of the voltage, frequency and refresh rate settings can also harness the inherent variability among the cores of the same multicore chip or the different DRAM DIMMs of a machine. Different accelerators architectures such as GPUs, FPGAs or other custom accelerator chips already used with state-of-art embedded and high performance systems can be similarly tuned to improve energy and performance efficiency.

An accurate identification and characterization of the voltage, frequency and refresh rate margins and their variability under various workload and environmental conditions can effectively drive software layers solutions for improved energy efficiency or performance, while the correctness/reliability of operation and the required quality-of-service level is preserved. To this aim, diligent communication between the hardware components of a computing system and the system software components that will take workload allocation and system operation integrity decisions are essential. Intelligent margins and variability aware software stack design can maximize the gains, while ensuring robust system operation.

This Special Issue of IEEE Transactions on Sustainable Computing will be covering this cross-layer research domain seeking three broad types of contributions: (a) novel methods and flows for the characterization and measurement of the pessimistic design margins and their variability across memory and processor chips and cores, (b) effective prediction and communication/reporting mechanisms to expose hardware margins and variability as well device behavior under non-nominal operating conditions to the software layers and (c) error-resilient software paradigms to harness the exposed margins and variability for improved energy-efficiency and/or performance.

Special Issue on Sustainable Information Security and Forensic Computing

Submission deadline: May 1, 2018. View PDF.

Modern societies are becoming increasingly reliance on inter-connected digital systems, where commercial activities and government services are delivered. Despite the benefits, it is impossible to overstate the importance of information security and forensics in a highly inter-connected system. To address security threats to network infrastructure devices and sensitive data, many different solutions capable of providing a suitable degree of security and forensic capability have been proposed. However, such solutions have not been properly designed to address important aspects such as computational costs, scalability, energy efficiency and resource usage. This special issue thus focuses on practical aspects of information security and forensics in sustainable computing. We solicit original contributions on novel threats, defences and security, information, tools, and digital forensics applications in sustainable computing. We also seek contributions motivated by taking real-world security and forensic problems and theoretical works that have clear intention for practical applications.

Special Issue on Sustainability of Fog/Edge Computing Systems

Submission deadline: May 31, 2018. View PDF.

Fog/Edge Computing is an emerging architectural as well as technical approach aimed at addressing various shortcomings in traditional cloud computing paradigms and responding to today’s constantly increasing data-demanding services such as Internet-of-Things, 5G embedded artificial intelligence and smart cities. In Fog/Edge Computing, nodes at the edge of a network are equipped with processing, storage, networking, etc. capabilities to take over several tasks that were used to be sent to cloud services. Pre-filtering and aggregation of data as well as online processing and actuation are sample procedures envisaged/dedicated to fog/edge nodes.

Although slightly different in the way they are implemented, fog and edge paradigms are designed in direct response to various challenges in operating smooth IoT and 5G services including –but not limited to: stringent latency requirements from sensing to actuation, network bandwidth limitation for large-sized aggregated data, limited resources for edge devices to perform tasks, and security requirements for all data flows and operations. Satisfying all aforementioned concerns becomes even more challenging when considering the rapid constant grow of edge devices/sensors. For example, the current number of IoT devices will rapidly increase from 15 billion to 50 billion by 2020 (according to CISCO), while the number of sensors will increase to as high as 1 trillion by 2030 (according to HP Labs). As a consequence, sustainability of such systems becomes a necessity rather than a luxury.

To address several major issues regarding sustainability of future fog/edge systems, this special issue aims at highlighting challenges, state-of-the-art, and solutions to a set of currently unresolved key questions including –but not limited to—performance, modelling, optimization, reliability, security, privacy and techno-economic aspects of fog/edge architectures. Through addressing these concerns while understanding their impacts and limitations, technological advancements will be channelled toward more sustainable/efficient platforms for tomorrow’s ever-connected systems.

Special Issue on Intelligent Data Analysis for Sustainable Computing

Submission deadline: September 1, 2018. View PDF.

Recent years have witnessed a deluge of new and big spatio-temporal data streams that contain a wealth of information relevant to sustainable development goals. The analysis of such data streams poses tremendous challenges in the current computing systems, due to its strong correlations between the temporal and spatial domain of the data, and the emerging needs of real-time decision support in some real-world problems.

To obtain this valuable information, there is an urgent demand for high-level computational intelligence based on emerging analytical techniques, such as big data analytics, Web analytics, and network analytics, employing software tools from advanced analytics disciplines, such as machine learning, data mining, and predictive analytics. This results in modern data analysis techniques having the potential to yield accurate, inexpensive, and high scalable models for providing intelligent and real-time decision support in creating effective computing systems. This will also result in addressing sustainability problems in computing and information processing environments at different levels of computational intelligence paradigms. Computational intelligent data analysis is playing an ever-increasingly important and critical role in achieving sustainable ICT (Information and Communication Technology) in new computing paradigms of the current data-driven era.

This special issue is devoted to the most recent developments and research outcomes addressing the related theoretical and practical aspects of computational intelligence solutions in sustainable computing and aims at presenting latest innovative ideas targeted at the corresponding key challenges, either from a methodological or from an application perspective.

Special Issue on Intersection of Computing and Communication Technologies with Energy Systems

Submission deadline: 15 Dec. 2018. View PDF.

Computing and communication technologies impact energy systems in two distinct ways. The exponential growth of these technologies has made them large energy consumers. Therefore, new architectures, technologies and systems are being developed and deployed to make computing and networked system more energy efficient. Additionally, these technologies will play a central role in the on-going transformation of our energy systems. They help measure, monitor and control energy resources, inform and shape human demand, and determine how utilities, generators, regulators, and consumers interact. Recently, there have been vibrant developments in the research community at the intersection of computing and communication technologies with energy systems. Diverse applications of computing and networked systems have made legacy systems more energy-efficient, as well as improved the design, analysis, and development of innovative new energy systems.

This special issue calls for novel ideas for shaping the future of this area. We seek high-quality papers at the intersection of computing and communication technologies with energy systems. We welcome submissions describing conceptual advances, as well as advances in system design, implementation and experimentation.

General Call for Papers

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