Temperature-Aware Design and Management for 3D Multi-Core Architectures

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The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

A de facto standard approach in solving computer vision tasks is to use a common high-resolution camera and choose its placement on an agent based on human intuition. On the other hand, extremely simple and well-designed visual sensors found throughout nat ...

In order to extract maximum surplus from a heterogeneous customer base it is common practice for firms to offer a portfolio of differentiated products, from which consumers of different preferences can select their favorite items. The standard model of pro ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Social Engagement is a novel business model whose goal is transforming final users of a service from passive components into active ones. In this framework, people are contacted by the decision-maker (generally a company) and they are asked to perform task ...

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 ...

The invention relates to an Imaging sensor device in a stacked arrangement comprising: - a pixel array tier comprising a plurality of pixel segments each having a plurality of pixels for photon detection each providing a digital pixel output; - a processin ...

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 ...

Silicon Nitride (Si3N4) photonic integrated circuits (PICs) have emerged as core technology in a variety of applications ranging from LIDAR to quantum control and computing. However, the need for high-speed, low-voltage tuning and modulation has been a lon ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

We present the design and implementation of RECA, a novel human-centric recommender system for co-optimizing energy consumption, comfort and air quality in commercial buildings. Existing works generally optimize these objectives separately, or by only cont ...

Several techniques have been proposed for automatically searching for FPGA switch-blocks which typically show some tangible advantage over the well-known academic architectures. However, the resulting switch-blocks usually exhibit high levels of irregulari ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Multi-Chiplet architectures are being increasingly adopted to support the design of very large systems in a single package, facilitating the integration of heterogeneous components and improving manufacturing yield. However, chiplet-based solutions have to ...

The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Artificial Intelligence (AI) techniques are considered the most advanced approaches for diagnosing faults in power transformers. Dissolved Gas Analysis (DGA) is the conventional approach widely adopted for diagnosing incipient faults in power transformers. ...

There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

Temperature-Aware Design and Management for 3D Multi-Core Architectures

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Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

How Far Can a 1-Pixel Camera Go? Solving Vision Tasks Using Photoreceptors and Computationally Designed Visual Morphology

Robust Optimization for Product Line Design

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Workforce Allocation for Social Engagement Services via Stochastic Optimization

Is the powersave governor really saving power?

Imaging sensor device using an array of single-photon avalanche diode photodetectors

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Programmable Silicon Nitride Photonic Integrated Circuits

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

RECA: A Multi-Task Deep Reinforcement Learning-Based Recommender System for Co-Optimizing Energy, Comfort and Air Quality in Commercial Buildings

Regularity Matters: Designing Practical FPGA Switch-Blocks

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

System-Level Exploration of In-Package Wireless Communication for Multi-Chiplet Platforms

Energy-Efficient Electronic Functions Based on the Co-integration of 2D and Ferroelectric Materials

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems

Power Transformer Fault Diagnosis Using Neural Network Optimization Techniques

Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization