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We present a new parallel model of computation suitable for spatial architectures, for which the energy used for communication heavily depends on the distance of the communicating processors. In our model, processors have locations on a…
The efficient deployment of Internet of Things (IoT) over cellular networks, such as Long Term Evolution (LTE) or the next generation 5G, entails several challenges. For massive IoT, reducing the energy consumption on the device side…
In order to meet the growing mobile data demand, future wireless networks will be equipped with a multitude of access points (APs). Besides the important implications for the energy consumption, the trend towards densification requires the…
Wireless ad hoc networks are power constrained since nodes operate with limited battery energy. Thus, energy consumption is crucial in the design of new ad hoc routing protocols. In order to maximize the lifetime of ad hoc networks, traffic…
We present distributed algorithms for training dynamic Graph Neural Networks (GNN) on large scale graphs spanning multi-node, multi-GPU systems. To the best of our knowledge, this is the first scaling study on dynamic GNN. We devise…
Dynamic Voltage and Frequency Scaling (DVFS), CPU pinning, horizontal, and vertical scaling, are four techniques that have been proposed as actuators to control the performance and energy consumption on data center servers. This work…
Deep neural networks (DNNs) have been widely applied in diverse applications, but the problems of high latency and energy overhead are inevitable on resource-constrained devices. To address this challenge, most researchers focus on the…
Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence, purely information-theoretic considerations fail to achieve the lowest energy per information bit…
In modern data centers, energy usage represents one of the major factors affecting operational costs. Power capping is a technique that limits the power consumption of individual systems, which allows reducing the overall power demand at…
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on…
Smartphones, laptops, and data centers are CMOS-based technologies that ushered our world into the information age of the 21st century. Despite their advantages for scalable computing, their implementations come with surprisingly large…
Reduction of wireless network energy consumption is becoming increasingly important to reduce environmental footprint and operational costs. A key concept to achieve it is the use of lean transmission techniques that dynamically…
With the advent of the Exascale capability allowing supercomputers to perform at least $10^{18}$ IEEE 754 Double Precision (64 bits) operations per second, many concerns have been raised regarding the energy consumption of high-performance…
The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…
With the increasing popularity of Internet-based services and applications, power efficiency is becoming a major concern for data center operators, as high electricity consumption not only increases greenhouse gas emissions, but also…
The amount of data moved over dedicated and non-dedicated network links increases much faster than the increase in the network capacity, but the current solutions fail to guarantee even the promised achievable transfer throughputs. In this…
Nowadays the number of available processing cores within computing nodes which are used in recent clustered environments, are growing up with a rapid rate. Despite this trend, the number of available network interfaces in such computing…
This paper presents a new cooperative wireless communication network strategy that incorporates energy cooperation and data cooperation. The model establishment, design goal formulations, and algorithms for throughput maximization of the…
With the increasing popularity of Cloud computing and Mobile computing, individuals, enterprises and research centers have started outsourcing their IT and computational needs to on-demand cloud services. Recently geographical load…
With the advent of edge computing, data generated by end devices can be pre-processed before transmission, possibly saving transmission time and energy. On the other hand, data processing itself incurs latency and energy consumption,…