Containergy-A Container-Based Energy and Performance Profiling Tool for Next Generation Workloads

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Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

The aluminium sector relies on natural gas for the conversion of recycled scrap into new feedstock, which results in substantial atmospheric emissions. Hydric resources are also impacted, as they serve as heat sinks for the waste heat generated during the ...

The TCV tokamak is powered by a flywheel generator to supply the magnetic coils and the auxiliary heating systems. The generator has just undergone its fourth major overhaul to make it ready for the next ten years, after more than thirty years of almost tr ...

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

The European Union's Green Deal aims for a 55% reduction in greenhouse gas emissions by 2030. To reach this goal, a massive integration of Renewable Energy Sources (RES) into the power grid is necessary. As RES become a large part of the electricity genera ...

SKIPTRAIN is a novel Decentralized Learning (DL) algorithm, which minimizes energy consumption in decentralized learning by strategically skipping some training rounds and substituting them with synchronization rounds. These trainingsilent periods, besides ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

Energy efficiency is crucial for the sustainable operation of industrial and urban sectors. However, practicing engineers seldom have access to open-source tools that can readily evaluate and compare scenarios. In this work, a novel web-based tool called R ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

In recent years, many efforts have been made to find alternative renewable energy sources that can ideally replace the use of fossil fuels in all aspects. One of the new emerging energy technologies is the bioelectrochemical system, of which two types are ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

Plant cells harness osmotic pressures to stiffen their leaves through strong turgor pressures. Key to this osmosisdriven stiffening is the confinement of liquids within semipermeable membranes that can regulate the transport of water molecules and ions. In ...

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly e ...

Smarty is a fully-reconfigurable on-chip feed-forward artificial neural network (ANN) with ten integrated time-to-digital converters (TDCs) designed in a 16 nm FinFET CMOS technology node. The integration of TDCs together with an ANN aims to reduce system ...

Containergy-A Container-Based Energy and Performance Profiling Tool for Next Generation Workloads

Chattez avec Graph Search

On the added value of sequential deep learning for the upscaling of evapotranspiration

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Is the powersave governor really saving power?

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Renewable energy integration and waste heat valorization in aluminum remelting for co-producing kerosene and methanol

Maintenance and optimization of the TCV power supply

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Electrical and Optical Manifestations of Flat Band Physics in Van der Waals Materials

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Extensions of Peer Prediction Incentive Mechanisms

Advanced control strategies to exploit the hydropower potential enhancing ancillary services provision to the power system

Energy-Aware Decentralized Learning with Intermittent Model Training

Secure Interface Design Leveraging Hardware/Software Support

ROSMOSE: A web-based decision support tool for the design and optimization of industrial and urban energy systems

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Green hydrogen production using Shewanella oneidensis MR-1 bioanode and cuprous oxide-based photocathode

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Osmosis-driven stiffening of structured hydrogels

Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer composites

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography