Related papers: Modelling Energy Consumption based on Resource Uti…
This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life…
Creating a model of a computer system that can be used for tasks such as predicting future resource usage and detecting anomalies is a challenging problem. Most current systems rely on heuristics and overly simplistic assumptions about the…
As AI inference scales to billions of queries and emerging reasoning and agentic workflows increase token demand, reliable estimates of per-query energy use are increasingly important for capacity planning, emissions accounting, and…
Reducing energy consumption is one of the key challenges in computing technology. One factor that contributes to high energy consumption is that all parts of the program are considered equally significant for the accuracy of the end-result.…
Electricity consumption forecasting has important implications for the mineral companies on guiding quarterly work, normal power system operation, and the management. However, electricity consumption prediction for the mineral company is…
As field-programmable gate arrays become prevalent in critical application domains, their power consumption is of high concern. In this paper, we present and evaluate a power monitoring scheme capable of accurately estimating the runtime…
The transition from traditional power grids to smart grids, significant increase in the use of renewable energy sources, and soaring electricity prices has triggered a digital transformation of the energy infrastructure that enables new,…
The use of steel is essential in many industries, including infrastructure, transportation, and modern architecture. Predicting power consumption in the steel industry is crucial to meet the rising demand for steel and promoting city…
This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system…
As the importance of eco-friendly transportation increases, providing an efficient approach for marine vessel operation is essential. Methods for status monitoring with consideration to the weather condition and forecasting with the use of…
The accelerated development of machine learning methods, primarily deep learning, are causal to the recent breakthroughs in medical image analysis and computer aided intervention. The resource consumption of deep learning models in terms of…
The microgrids design for remote locations represents one of the most important and critical applications of the microgrid concept. It requires the correct sizing and the proper utilization of the different sources to guarantee the…
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…
In the current high-performance and embedded computing era, full-stack energy-centric design is paramount. Use cases require increasingly high performance at an affordable power budget, often under real-time constraints. Extreme…
In science, problems in many fields can be solved by processing datasets using a series of computationally expensive algorithms, sometimes referred to as workflows. Traditionally, the configurations of these workflows are optimized to…
There is growing interest in lowering the energy consumption of computation. Energy transparency is a concept that makes a program's energy consumption visible from software to hardware through the different system layers. Such transparency…
Computing has a huge memory problem. The memory system, consisting of multiple technologies at different levels, is responsible for most of the energy consumption, performance bottlenecks, robustness problems, monetary cost, and hardware…
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…
In recent years, a number of major improvements were introduced in the area of computer networks, energy-efficient network protocols and network management systems. Software Defined Networking (SDN) as a new paradigm for managing complex…
The increase in performance and power of computing systems requires the wider use of program optimizations. The goal of performing optimizations is not only to reduce program runtime, but also to reduce other computer resources including…