activity
20142026
most citedThe IoT energy challenge: A software perspective

102 citations · 323 across the 21 of their papers we have counts for

collaborators

22 papers

math.NA2026

Learning Contractive Integral Operators with Fredholm Integral Neural Operators

Kyriakos C. Georgiou, Constantinos Siettos, Athanasios N. Yannacopoulos

We generalize the framework of Fredholm Neural Networks, to learn non-expansive integral operators arising in Fredholm Integral Equations (FIEs) of the second kind in arbitrary dim…

math.NA2025

HEATNETs: Explainable Random Feature Neural Networks for High-Dimensional Parabolic PDEs

Kyriakos Georgiou, Gianluca Fabiani, Constantinos Siettos +1

We deal with the solution of the forward problem for high-dimensional parabolic PDEs with random feature (projection) neural networks (RFNNs). We first prove that there exists a si…

math.NA2025

Fredholm Neural Networks for inverse problems in elliptic PDEs

Kyriakos C. Georgiou, Constantinos Siettos, Athanasios N. Yannacopoulos

Building on our previous work on Fredholm Neural Networks (Fredholm NNs/ FNNs) for solving integral equations, we extend the framework to inverse problems for linear and nonlinear…

math.NA2024★ 3 cited

Fredholm Neural Networks

Kyriakos Georgiou, Constantinos Siettos, Athanasios N. Yannacopoulos

Within the family of explainable machine-learning, we present Fredholm neural networks (Fredholm NNs): deep neural networks (DNNs) architectures motivated by fixed-point iteration…

q-fin.RM2023★ 1 cited

Probability of Default modelling with Lévy-driven Ornstein-Uhlenbeck processes and applications in credit risk under the IFRS 9

Kyriakos Georgiou, Athanasios N. Yannacopoulos

In this paper we develop a framework for estimating Probability of Default (PD) based on stochastic models governing an appropriate asset value processes. In particular, we build u…

cs.SE2023★ 7 cited

Accurate Energy Modelling on the Cortex-M0 Processor for Profiling and Static Analysis

Kris Nikov, Kyriakos Georgiou, Zbigniew Chamski +2

Energy modelling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processor…

cs.AR2022★ 5 cited

Evaluating the effects of reducing voltage margins for energy-efficient operation of MPSoCs

Diego V. Cirilo do Nascimento, Kyriakos Georgiou, Kerstin I. Eder +1

Voltage margins, or guardbands, are imposed on DVFS systems to account for process, voltage, and temperature variability effects. While necessary to assure correctness, guardbands…

cs.CR2021

Security-Hardening Software Libraries with Ada and SPARK -- A TCP Stack Use Case

Kyriakos Georgiou, Guillaume Cluzel, Paul Butcher +1

This white paper demonstrates how the assurance, reliability, and security of an existing professional-grade, open-source embedded TCP/IP stack implementation written in the C prog…

cs.DC2021★ 10 cited

Robust and accurate fine-grain power models for embedded systems with no on-chip PMU

Kris Nikov, Marcos Martinez, Simon Wegener +4

This paper presents a novel approach to event-based power modelling for embedded platforms that do not have a Performance Monitoring Unit (PMU). The method involves complementing t…

cs.SE2021★ 5 cited

A Comprehensive and Accurate Energy Model for Arm's Cortex-M0 Processor

Kyriakos Georgiou, Zbigniew Chamski, Kris Nikov +1

Energy modeling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processors…

eess.SY2020★ 24 cited

Performance and Energy Trade-Offs for Parallel Applications on Heterogeneous Multi-Processing Systems

Demetrios A. M. Coutinho, Daniele De Sensi, Arthur Francisco Lorenzon +4

This work proposes a methodology to find performance and energy trade-offs for parallel applications running on Heterogeneous Multi-Processing systems with a single instruction-set…

cs.DC2019★ 12 cited

When parallel speedups hit the memory wall

Alex F. A. Furtunato, Kyriakos Georgiou, Kerstin Eder +1

After Amdahl's trailblazing work, many other authors proposed analytical speedup models but none have considered the limiting effect of the memory wall. These models exploited aspe…

cs.PL2019★ 8 cited

Lost in translation: Exposing hidden compiler optimization opportunities

Kyriakos Georgiou, Zbigniew Chamski, Andres Amaya Garcia +2

Existing iterative compilation and machine-learning-based optimization techniques have been proven very successful in achieving better optimizations than the standard optimization…

cs.DC2018

Energy-Optimal Configurations for Single-Node HPC Applications

Vitor R. G. Silva, Alex Furtunato, Kyriakos Georgiou +2

Energy efficiency is a growing concern for modern computing, especially for HPC due to operational costs and the environmental impact. We propose a methodology to find energy-optim…

cs.PF2018★ 16 cited

Less is More: Exploiting the Standard Compiler Optimization Levels for Better Performance and Energy Consumption

Kyriakos Georgiou, Craig Blackmore, Samuel Xavier-de-Souza +1

This paper presents the interesting observation that by performing fewer of the optimizations available in a standard compiler optimization level such as -O2, while preserving thei…

cs.DC2017

The Benefits of Low Operating Voltage Devices to the Energy Efficiency of Parallel Systems

Samuel Xavier-de-Souza, Eduardo A. Neves, Alex F. A. Furtunato +3

Programmable circuits such as general-purpose processors or FPGAs have their end-user energy efficiency strongly dependent on the program that they execute. Ultimately, it is the p…

cs.SE2017★ 102 cited

The IoT energy challenge: A software perspective

Kyriakos Georgiou, Samuel Xavier-de-Souza, Kerstin Eder

The Internet of Things (IoT) sparks a whole new world of embedded applications. Most of these applications are based on deeply embedded systems that have to operate on limited or u…

cs.OH2016★ 28 cited

Energy Transparency for Deeply Embedded Programs

Kyriakos Georgiou, Steve Kerrison, Zbigniew Chamski +1

Energy transparency is a concept that makes a program's energy consumption visible, from hardware up to software, through the different system layers. Such transparency can enable…

cs.AR2016★ 21 cited

ENTRA: Whole-Systems Energy Transparency

Kerstin Eder, John P. Gallagher, Pedro Lopez-Garcia +14

Promoting energy efficiency to a first class system design goal is an important research challenge. Although more energy-efficient hardware can be designed, it is software that con…

cs.PL2015★ 17 cited

Inferring Parametric Energy Consumption Functions at Different Software Levels: ISA vs. LLVM IR

Umer Liqat, Kyriakos Georgiou, Steve Kerrison +4

The static estimation of the energy consumed by program executions is an important challenge, which has applications in program optimization and verification, and is instrumental i…

cs.PL2015★ 4 cited

On the Value and Limits of Multi-level Energy Consumption Static Analysis for Deeply Embedded Single and Multi-threaded Programs

Kyriakos Georgiou, Steve Kerrison, Kerstin Eder

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 har…

cs.PL2014★ 60 cited

Static analysis of energy consumption for LLVM IR programs

Neville Grech, Kyriakos Georgiou, James Pallister +3

Energy models can be constructed by characterizing the energy consumed by executing each instruction in a processor's instruction set. This can be used to determine how much energy…