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Geoff V. Merrett - IEEE Xplore Author Profile
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Geoff V. Merrett

Also published under: Geoff Merrett

Publications
106
Citations
1,716
Publications by Year
20062024
Co-Authors:
Show All Co-Authors (152)
Image of author Geoff V. Merrett

Geoff V. Merrett

Also published under: Geoff Merrett

Affiliation

School of Electronics and Computer Science, University of Southampton, UK

Publication Topics

Biography

Geoff V. Merrett is a Professor of electronic and software systems with the School of Electronics and Computer Science, University of Southampton, Southampton, U.K. His research interests are in energy management of mobile and embedded systems, and he has published over 200 articles in these areas.(Based on document published on 23 March 2020).
Publications
106
Citations
1,716
Publications by Year
20062024
Co-Authors:
Show All Co-Authors (152)
Author's Published Works

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Realisation of Early-Exit Dynamic Neural Networks on Reconfigurable Hardware

Anastasios Dimitriou;Lei Xun;Jonathon Hare;Geoff V. Merrett

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2024 | Early Access Article |
Early-Exiting is a strategy that’s becoming popular in Deep Neural Networks (DNNs), as it can lead to faster execution and a reduction in the computational intensity of inference. To achieve this, intermediate classifiers abstract information from the input samples to strategically stop forward propagation and generate an output at an earlier stage. Confidence criteria are used to identify easier-...Show More

Realisation of Early-Exit Dynamic Neural Networks on Reconfigurable Hardware

Anastasios Dimitriou;Lei Xun;Jonathon Hare;Geoff V. Merrett

Year: 2024 | Early Access Article |

Evaluating Routing Protocols for Intermittent Energy Harvesting IoT Networks

Sara A. Alsodairi;Alex S. Weddell;Nawfal F. Al Hashimy;Geoff V. Merrett

2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS)
Year: 2024 | Conference Paper |
Internet of Things (IoT) applications have evolved rapidly in the last few years, many of which use small, pervasive and locally-powered sensing devices. Energy harvesting techniques help to extend the lifetime of these devices. These devices can only work intermittently during power cycles when energy is available, but this is not taken into account by traditional routing protocols. Opportunistic...Show More

Evaluating Routing Protocols for Intermittent Energy Harvesting IoT Networks

Sara A. Alsodairi;Alex S. Weddell;Nawfal F. Al Hashimy;Geoff V. Merrett

Year: 2024 | Conference Paper |

FPGA Acceleration of Dynamic Neural Networks: Challenges and Advancements

Anastasios Dimitriou;Benjamin Biggs;Jonathon Hare;Geoff V. Merrett

2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS)
Year: 2024 | Conference Paper |
Modern machine learning methods continue to produce models with a high memory footprint and computational complexity that are increasingly difficult to deploy in resource constrained environments. This is, in part, driven by a focus on costly, power-intensive GPUs, which has a feedback effect on the variety of methods and models chosen for development. We advocate for a transition away from the ge...Show More

FPGA Acceleration of Dynamic Neural Networks: Challenges and Advancements

Anastasios Dimitriou;Benjamin Biggs;Jonathon Hare;Geoff V. Merrett

Year: 2024 | Conference Paper |

Fluid Dynamic DNNs for Reliable and Adaptive Distributed Inference on Edge Devices

Lei Xun;Mingyu Hu;Hengrui Zhao;Amit Kumar Singh;Jonathon Hare;Geoff V. Merrett

2024 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Year: 2024 | Conference Paper |
Distributed inference is a popular approach for efficient DNN inference at the edge. However, traditional Static and Dynamic DNNs are not distribution-friendly, causing system reliability and adaptability issues. In this paper, we introduce Fluid Dynamic DNNs (Fluid DyDNNs), tailored for distributed inference. Distinct from Static and Dynamic DNNs, Fluid DyDNNs utilize a novel nested incremental t...Show More

Fluid Dynamic DNNs for Reliable and Adaptive Distributed Inference on Edge Devices

Lei Xun;Mingyu Hu;Hengrui Zhao;Amit Kumar Singh;Jonathon Hare;Geoff V. Merrett

Year: 2024 | Conference Paper |

Enabling ImageNet-Scale Deep Learning on MCUs for Accurate and Efficient Inference

Sulaiman Sadiq;Jonathon Hare;Simon Craske;Partha Maji;Geoff Merrett

IEEE Internet of Things Journal
Year: 2024 | Volume: 11, Issue: 7 | Journal Article |
Cited by: Papers (3)
Conventional approaches to Tiny Machine Learning (TinyML) achieve high accuracy by deploying the largest deep learning model with the highest input resolutions that fit within the size constraints imposed by the microcontroller’s (MCUs) fast internal storage and memory. In this article, we perform an in-depth analysis of prior works to show that models derived within these constraints suffer from ...Show More

Enabling ImageNet-Scale Deep Learning on MCUs for Accurate and Efficient Inference

Sulaiman Sadiq;Jonathon Hare;Simon Craske;Partha Maji;Geoff Merrett

Year: 2024 | Volume: 11, Issue: 7 | Journal Article |

FedTM: Memory and Communication Efficient Federated Learning with Tsetlin Machine

Shannon Shi Qi How;Jagmohan Chauhan;Geoff V Merrett;Jonathan Hare

2023 International Symposium on the Tsetlin Machine (ISTM)
Year: 2023 | Conference Paper |
Federated Learning has been an exciting development in machine learning, promising collaborative learning without compromising privacy. However, the resource-intensive nature of Deep Neural Networks (DNN) has made it difficult to implement FL on edge devices. In a bold step towards addressing this challenge, we present FedTM, the first FL framework to utilize Tsetlin Machine, a low-complexity mach...Show More

FedTM: Memory and Communication Efficient Federated Learning with Tsetlin Machine

Shannon Shi Qi How;Jagmohan Chauhan;Geoff V Merrett;Jonathan Hare

Year: 2023 | Conference Paper |

Energy-Efficient Memory Tracing for State Retention in Transient Computing Systems

Theodoros D. Verykios;Domenico Balsamo;Geoff V. Merrett

2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
Transient computing systems, also known as intermittent computing systems, are batteryless systems powered by energy harvesting (EH) sources that do not require large energy storage for system operations. Instead, they rely on retaining their state, i.e. a snapshot, in non-volatile memory (NVM) in the event of a power outage and restoring it when the power recovers. In this paper, we first discuss...Show More

Energy-Efficient Memory Tracing for State Retention in Transient Computing Systems

Theodoros D. Verykios;Domenico Balsamo;Geoff V. Merrett

Year: 2023 | Conference Paper |

Content- and Lighting-Aware Adaptive Brightness Scaling for Improved Mobile User Experience

Samuel Isuwa;David Amos;Amit Kumar Singh;Bashir M. Al-Hashimi;Geoff V. Merrett

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Year: 2023 | Conference Paper |
For an improved user experience, the display sub-system is expected to provide superior resolution and optimal brightness despite its impact on battery life. Existing brightness scaling approaches set the display brightness statically or adaptively in response to predefined events such as low-battery or ambient light of the environment, which are independent of the displayed content. Approaches th...Show More

Content- and Lighting-Aware Adaptive Brightness Scaling for Improved Mobile User Experience

Samuel Isuwa;David Amos;Amit Kumar Singh;Bashir M. Al-Hashimi;Geoff V. Merrett

Year: 2023 | Conference Paper |

Exploration of Decision Sub-Network Architectures for FPGA-based Dynamic DNNs

Anstasios Dimitriou;Mingyu Hu;Jonathon Hare;Geoff V. Merrett

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Dynamic Deep Neural Networks (DNNs) can achieve faster execution and less computationally intensive inference by spending fewer resources on easy to recognise or less informative parts of an input. They make data-dependent decisions, which strategically deactivate a model's components, e.g. layers, channels or sub-networks. However, dynamic DNNs have only been explored and applied on conventional ...Show More

Exploration of Decision Sub-Network Architectures for FPGA-based Dynamic DNNs

Anstasios Dimitriou;Mingyu Hu;Jonathon Hare;Geoff V. Merrett

Year: 2023 | Conference Paper |

Pragmatic Memory-System Support for Intermittent Computing Using Emerging Nonvolatile Memory

Sivert T. Sliper;William Wang;Nikos Nikoleris;Alex S. Weddell;Anand Savanth;Pranay Prabhat;Geoff V. Merrett

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2023 | Volume: 42, Issue: 1 | Journal Article |
Cited by: Papers (6)
Intermittent computing (IC) is a key enabler for the vision of a trillion Internet of Things devices. By harvesting energy from the environment and leveraging nonvolatile memory (NVM) to retain computational progress across power cycles, IC enables untethered and battery-free devices to perform computation whenever ambient energy is available. The backbone of state retention is NVM, and recent adv...Show More

Pragmatic Memory-System Support for Intermittent Computing Using Emerging Nonvolatile Memory

Sivert T. Sliper;William Wang;Nikos Nikoleris;Alex S. Weddell;Anand Savanth;Pranay Prabhat;Geoff V. Merrett

Year: 2023 | Volume: 42, Issue: 1 | Journal Article |

Multi-Source Multi-Destination Hybrid Infrastructure-Aided Traffic Aware Routing in V2V/I Networks

Teodor Ivanescu;Halil Yetgin;Geoff V. Merrett;Mohammed El-Hajjar

IEEE Access
Year: 2022 | Volume: 10 | Journal Article |
Cited by: Papers (2)
The concept of the “connected car” offers the potential for safer, more enjoyable and more efficient driving and eventually autonomous driving. However, in urban Vehicular Networks (VNs), the high mobility of vehicles along roads poses major challenges to the routing protocols needed for a reliable and flexible vehicular communications system. Thus, urban VNs rely on static Road-Side-Units (RSUs) ...Show More

Multi-Source Multi-Destination Hybrid Infrastructure-Aided Traffic Aware Routing in V2V/I Networks

Teodor Ivanescu;Halil Yetgin;Geoff V. Merrett;Mohammed El-Hajjar

Year: 2022 | Volume: 10 | Journal Article |

TinyOps: ImageNet Scale Deep Learning on Microcontrollers

Sulaiman Sadiq;Jonathon Hare;Partha Maji;Simon Craske;Geoff V. Merrett

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Deep Learning on microcontroller (MCU) based IoT devices is extremely challenging due to memory constraints. Prior approaches focus on using internal memory or external memories exclusively which limit either accuracy or latency. We find that a hybrid method using internal and external MCU memories outperforms both approaches in accuracy and latency. We develop TinyOps, an inference engine which a...Show More

TinyOps: ImageNet Scale Deep Learning on Microcontrollers

Sulaiman Sadiq;Jonathon Hare;Partha Maji;Simon Craske;Geoff V. Merrett

Year: 2022 | Conference Paper |

Mesh Networking for Intermittently Powered Devices: Architecture and Challenges

Edward Longman;Oktay Cetinkaya;Mohammed El-Hajjar;Geoff V. Merrett

IEEE Network
Year: 2022 | Volume: 36, Issue: 3 | Magazine Article |
Cited by: Papers (4)
Recent advances in low-power computing enable energy harvesting-powered devices, even in energy scarce conditions. This reduces the reliance on batteries in Internet of Things devices, reducing the cost and enabling new application domains. However, energy scarcity requires devices to operate intermittently, with minimal stored energy and where high-cost radio frequency (RF) communication dominate...Show More

Mesh Networking for Intermittently Powered Devices: Architecture and Challenges

Edward Longman;Oktay Cetinkaya;Mohammed El-Hajjar;Geoff V. Merrett

Year: 2022 | Volume: 36, Issue: 3 | Magazine Article |

Similarity-Aware CNN for Efficient Video Recognition at the Edge

Amin Sabet;Jonathon Hare;Bashir M. Al-Hashimi;Geoff V. Merrett

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2022 | Volume: 41, Issue: 11 | Journal Article |
Cited by: Papers (2)
Convolutional neural networks (CNNs) often extract similar features from successive video frames due to having identical appearances. In contrast, conventional CNNs for video recognition process individual frames with a fixed computational effort. Each video frame is independently processed, resulting in numerous redundant computations and an inefficient use of limited energy resources, particular...Show More

Similarity-Aware CNN for Efficient Video Recognition at the Edge

Amin Sabet;Jonathon Hare;Bashir M. Al-Hashimi;Geoff V. Merrett

Year: 2022 | Volume: 41, Issue: 11 | Journal Article |

A High-Level Approach for Energy Efficiency Improvement of FPGAs by Voltage Trimming

Mehdi Safarpour;Lei Xun;Geoff V. Merrett;Olli Silvén

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2022 | Volume: 41, Issue: 10 | Journal Article |
Cited by: Papers (4)
Chip manufacturers define voltage margins on top of the “best-case” operational voltage of their chips to ensure reliable functioning in the worst-case settings. The margins guarantee correctness of operation, but at the cost of performance and power efficiency. Violating the margins is tempting to save energy, but might lead to timing errors. This article proposes an algorithmic solution that ena...Show More

A High-Level Approach for Energy Efficiency Improvement of FPGAs by Voltage Trimming

Mehdi Safarpour;Lei Xun;Geoff V. Merrett;Olli Silvén

Year: 2022 | Volume: 41, Issue: 10 | Journal Article |

Exploring the Effect of Energy Storage Sizing on Intermittent Computing System Performance

Jie Zhan;Geoff V. Merrett;Alex S. Weddell

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2022 | Volume: 41, Issue: 3 | Journal Article |
Cited by: Papers (3)
Batteryless energy-harvesting devices promise to deliver a sustainable Internet of Things. Intermittent computing is an emerging area, where the application forward progress, i.e., computation beneficial to the progress of the active application, is maintained by saving the volatile computing state into nonvolatile memory before power interruptions, and restored afterward. Conventional intermitten...Show More

Exploring the Effect of Energy Storage Sizing on Intermittent Computing System Performance

Jie Zhan;Geoff V. Merrett;Alex S. Weddell

Year: 2022 | Volume: 41, Issue: 3 | Journal Article |

Emergent Design Challenges for Embedded Systems and Paths Forward: Mixed-criticality, Energy, Reliability and Security Perspectives: Special Session Paper

Siva Satyendra Sahoo;Akash Kumar;Martin Decky;Samuel C.B. Wong;Geoff V. Merrett;Yinyuan Zhao;Jiachen Wang;Xiaohang Wang;Amit Kumar Singh

2021 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Modern embedded systems need to cater for several needs depending upon the application domain in which they are deployed. For example, mixed-critically needs to be considered for real-time and safety-critical systems and energy for battery-operated systems. At the same time, many of these systems demand for their reliability and security as well. With electronic systems being used for increasingly...Show More

Emergent Design Challenges for Embedded Systems and Paths Forward: Mixed-criticality, Energy, Reliability and Security Perspectives: Special Session Paper

Siva Satyendra Sahoo;Akash Kumar;Martin Decky;Samuel C.B. Wong;Geoff V. Merrett;Yinyuan Zhao;Jiachen Wang;Xiaohang Wang;Amit Kumar Singh

Year: 2021 | Conference Paper |

Dynamic Transformer for Efficient Machine Translation on Embedded Devices

Hishan Parry;Lei Xun;Amin Sabet;Jia Bi;Jonathon Hare;Geoff V. Merrett

2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
The Transformer architecture is widely used for machine translation tasks. However, its resource-intensive nature makes it challenging to implement on constrained embedded devices, particularly where available hardware resources can vary at run-time. We propose a dynamic machine translation model that scales the Transformer architecture based on the available resources at any particular time. The ...Show More

Dynamic Transformer for Efficient Machine Translation on Embedded Devices

Hishan Parry;Lei Xun;Amin Sabet;Jia Bi;Jonathon Hare;Geoff V. Merrett

Year: 2021 | Conference Paper |

Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms

Wei Lou;Lei Xun;Amin Sabet;Jia Bi;Jonathon Hare;Geoff V. Merrett

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2021 | Conference Paper |
Cited by: Papers (19)
Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At run-time, the available hardware resources to DNNs can vary considerably due to other concurrently running applications. The performance requirements of the applications could also change under different scenarios. To achieve the desired perform...Show More

Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms

Wei Lou;Lei Xun;Amin Sabet;Jia Bi;Jonathon Hare;Geoff V. Merrett

Year: 2021 | Conference Paper |

Wake-up Radio-enabled Intermittently-powered Devices for Mesh Networking: A Power Analysis

Edward Longman;Oktay Cetinkaya;Mohammed El-Hajjar;Geoff V. Merrett

2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
This paper analyzes the successful communication probability between two intermittently-powered nodes in a homogeneous energy harvesting (EH) mesh network. Powering devices using EH can enable networks to operate indefinitely; however, with limited energy storage and in scarce EH conditions, nodes may only be intermittently-powered. This reduces the effectiveness of conventional networking techniq...Show More

Wake-up Radio-enabled Intermittently-powered Devices for Mesh Networking: A Power Analysis

Edward Longman;Oktay Cetinkaya;Mohammed El-Hajjar;Geoff V. Merrett

Year: 2021 | Conference Paper |

Improving the Forward Progress of Transient Systems

Tim Daulby;Anand Savanth;Geoff V. Merrett;Alex S. Weddell

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2021 | Volume: 40, Issue: 3 | Journal Article |
Cited by: Papers (5)
Emerging applications for Internet of Things (IoT) devices demand smaller mass, size, and cost whilst increasing capability and reliability. Energy harvesting can provide power to these ultra-constrained devices, but introduces unreliability, unpredictability, and intermittency. Schemes for wireless sensors without batteries or supercapacitors overcome intermittency through saving system state int...Show More

Improving the Forward Progress of Transient Systems

Tim Daulby;Anand Savanth;Geoff V. Merrett;Alex S. Weddell

Year: 2021 | Volume: 40, Issue: 3 | Journal Article |

Mitigating Interactive Performance Degradation From Mobile Device Thermal Throttling

James R. B. Bantock;Bashir M. Al-Hashimi;Geoff V. Merrett

IEEE Embedded Systems Letters
Year: 2021 | Volume: 13, Issue: 1 | Journal Article |
Cited by: Papers (4)
Mobile devices are limited in mass and volume, reducing the viability of active device cooling implementations. This requires the use of less effective passive techniques to maintain device skin temperature levels. Application performance demands on a modern mobile device are driven by sustained performance workloads, such as 3-D games, virtual, and augmented reality. Mobile system-on-chips (SoCs)...Show More

Mitigating Interactive Performance Degradation From Mobile Device Thermal Throttling

James R. B. Bantock;Bashir M. Al-Hashimi;Geoff V. Merrett

Year: 2021 | Volume: 13, Issue: 1 | Journal Article |

Fused: Closed-Loop Performance and Energy Simulation of Embedded Systems

Sivert T. Sliper;William Wang;Nikos Nikoleris;Alex S. Weddell;Geoff V. Merrett

2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Year: 2020 | Conference Paper |
Cited by: Papers (16)
Energy-driven computing is an emerging paradigm that aims to fuel the proliferation of tiny and low-cost IoT sensing and monitoring devices. Energy-driven computers are generally powered by energy harvesting sources, and adapt their operation at runtime according to energy availability; thus, they must be designed and tested according to the expected dynamics of their power source. However, today'...Show More

Fused: Closed-Loop Performance and Energy Simulation of Embedded Systems

Sivert T. Sliper;William Wang;Nikos Nikoleris;Alex S. Weddell;Geoff V. Merrett

Year: 2020 | Conference Paper |

Efficient Deployment of UAV-powered Sensors for Optimal Coverage and Connectivity

Oktay Cetinkaya;Geoff V. Merrett

2020 IEEE Wireless Communications and Networking Conference (WCNC)
Year: 2020 | Conference Paper |
Cited by: Papers (13)
The Internet of Things (IoT) digitizes the physical world with wireless devices sensing their surroundings and delivering periodic notifications of parameters they are monitoring. However, this operation is bound by finite-capacity batteries, in which replenishment is practically infeasible due to the envisioned size of the IoT networks. By also considering the autonomous and self-sufficient servi...Show More

Efficient Deployment of UAV-powered Sensors for Optimal Coverage and Connectivity

Oktay Cetinkaya;Geoff V. Merrett

Year: 2020 | Conference Paper |

Optimising Resource Management for Embedded Machine Learning

Lei Xun;Long Tran-Thanh;Bashir M Al-Hashimi;Geoff V. Merrett

2020 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Year: 2020 | Conference Paper |
Cited by: Papers (10)
Machine learning inference is increasingly being executed locally on mobile and embedded platforms, due to the clear advantages in latency, privacy and connectivity. In this paper, we present approaches for online resource management in heterogeneous multi-core systems and show how they can be applied to optimise the performance of machine learning work-loads. Performance can be defined using plat...Show More

Optimising Resource Management for Embedded Machine Learning

Lei Xun;Long Tran-Thanh;Bashir M Al-Hashimi;Geoff V. Merrett

Year: 2020 | Conference Paper |

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