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We investigate an approach that uses low-level analysis and the execution-cache-memory (ECM) performance model in combination with tuning of hardware parameters to lower energy requirements of memory-bound applications. The ECM model is…
As supercomputers grow in size and complexity, power efficiency has become a critical challenge, particularly in understanding GPU power consumption within modern HPC workloads. This work addresses this challenge by presenting a data…
In this letter, a novel wireless powered protocol is proposed to maximize the system throughput of an energy harvesting (EH) based cognitive radio network, while satisfying a minimum primary user rate requirement. For EH, we exploit both…
Multi-access Edge Computing (MEC) delivers low-latency services by hosting applications near end-users. To promote sustainability, these systems are increasingly integrated with renewable Energy Harvesting (EH) technologies, enabling…
For various reasons including those related to climate changes, {\em energy} has become a critical concern in all relevant activities and technical designs. For the specific case of computer activities, the problem is exacerbated with the…
In this paper we study the power-performance relationship of power-efficient computing from a queuing theoretic perspective. We investigate the interplay of several system operations including processing speed, system on/off decisions, and…
Mobile Edge Computing (MEC) enables rich services in close proximity to the end users to provide high quality of experience (QoE) and contributes to energy conservation compared with local computing, but results in increased communication…
The energy footprint of global data movement has surpassed 100 terawatt hours, costing more than 20 billion US dollars to the world economy. Depending on the number of switches, routers, and hubs between the source and destination nodes,…
Energy-efficiency is a key concern for neural network applications. To alleviate this issue, hardware acceleration using FPGAs or GPUs can provide better energy-efficiency than general-purpose processors. However, further improvement of the…
Mobile edge computing (MEC) has recently become a prevailing technique to alleviate the intensive computation burden in Internet of Things (IoT) networks. However, the limited device battery capacity and stringent spectrum resource…
Fast wireless access has rapidly become commonplace. Wireless access points and Hotspot servers are sprouting everywhere. Battery lifetime continues to be a critical issue in mobile computing. This paper first gives an overview of WLAN…
Edge computing has emerged as a pivotal technology, offering significant advantages such as low latency, enhanced data security, and reduced reliance on centralized cloud infrastructure. These benefits are crucial for applications requiring…
Multi-Access Edge Computing (MEC) is a paradigm for handling delay sensitive services that require ultra-low latency at the access network. With it, computing and communications are performed within one Base Station (BS) site, where the…
High energy consumption of artificial intelligence has gained momentum worldwide, which necessitates major investments on expanding efficient and carbon-neutral generation and data center infrastructure in electric power grids. Going beyond…
The security and privacy concerns along with the amount of data that is required to be processed on regular basis has pushed processing to the edge of the computing systems. Deploying advanced Neural Networks (NN), such as deep neural…
One of the main concerns in traditional Wireless Sensor Networks (WSNs) is energy efficiency. In this work, we analyze two techniques that can extend network lifetime. The first is Ambient \emph{Energy Harvesting} (EH), i.e., the capability…
This work offers a heuristic evaluation of the effects of variations in machine learning training regimes and learning paradigms on the energy consumption of computing, especially HPC hardware with a life-cycle aware perspective. While…
Edge Computing enables low-latency processing for real-time applications but introduces challenges in power management due to the distributed nature of edge devices and their limited energy resources. This paper proposes a stochastic…
In wireless network communication environments, Spectral Efficiency (SE) and Energy Efficiency (EE) are among the major indicators used for evaluating network performance. However, given the high demand for data rate services and the…
The continuous growth of big data applications with high computational and scalability demands has resulted in increasing popularity of cloud computing. Optimizing the performance and power consumption of cloud resources is therefore…