相关论文: WattScope: Non-intrusive Application-level Power D…

Datacenters are vital to our digital society, but consume a considerable fraction of global electricity and demand is projected to increase. To improve their sustainability and performance, we envision that simulators will become primary…

Fine-grained power monitoring of software activities becomes unavoidable to maximize the power usage efficiency of data centers. In particular, achieving an optimal scheduling of containers requires the deployment of software-defined…

The rapid adoption of AI and convenience offered by cloud services have resulted in the growing demands for GPUs in the cloud. Generally, GPUs are physically attached to host servers as PCIe devices. However, the fixed assembly combination…

Load disaggregation techniques infer the operation of different power consuming devices from a single measurement point that records the total power draw over time. Thus, a device consuming power at the moment can be understood as…

The rapid urbanization of developing countries coupled with explosion in construction of high rising buildings and the high power usage in them calls for conservation and efficient energy program. Such a program require monitoring of…

Individual device loads and energy consumption feedback is one of the important approaches for pursuing users to save energy in residences. This can help in identifying faulty devices and wasted energy by devices when left On unused. The…

Data centers energy demand is increasing. While a great deal of effort has been made to reduce the amount of CO$_2$ generated by large cloud providers, too little has been done from the application perspective. We claim that application…

As datacenters continue to grow in scale, their energy consumption and resulting carbon footprint have become pressing concerns. With the increasing share of renewable energy in a datacenter's mixed energy supply, shifting task execution to…

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud…

Smart energy management based on the Internet of Things (IoT) aims to achieve optimal energy utilization through real-time energy monitoring and analyses of power consumption patterns in IoT networks (e.g., residential homes and offices)…

Scale-out workloads like media streaming or Web search serve millions of users and operate on a massive amount of data, and hence, require enormous computational power. As the number of users is increasing and the size of data is expanding,…

The overall performance of the development of computing systems has been engrossed on enhancing demand from the client and enterprise domains. but, the intake of ever-increasing energy for computing systems has commenced to bound in…

Data centers have become one of the major energy consumers, making their low-carbon operations critical to achieving global carbon neutrality. Although distributed data centers have the potential to reduce costs and emissions through…

Diversification of digital applications and workloads has driven the development of diverse datacenter architectures on ever-larger scales. These datacenters consist of complex IT, power, and cooling systems with interdependencies that…

Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing…

The exploding power consumption of AI and cloud datacenters (DCs) intensifies the long-standing concerns about their carbon footprint, especially because DCs' need for constant power clashes with volatile renewable generation needed for…

The Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data…

With weather becoming more extreme both in terms of longer dry periods and more severe rain events, municipal water networks are increasingly under pressure. The effects include damages to the pipes, flash floods on the streets and combined…

While the large energy consumption of Large Language Models (LLMs) is recognized by the community, system operators lack guidance for energy-efficient LLM inference deployments that leverage energy trade-offs of heterogeneous hardware due…

The escalating computational demands and energy footprint of GPU-accelerated computing systems complicate informed design and operational decisions. We present the first release of Wattlytics (https://wattlytics.netlify.app), an…