RAPID: ReAl-time Process ModellIng and Diagnostics: Powering Digital Factories

This projects aims to develop algorithms for real-time processing for analytics in digital factories. A particular use case is the design of hardware circuits, where silicon can easily be damaged during manufacturing. The production defects that arise negatively affect yield and/or quality of the devices. Uncovering these defects, and how they may be mitigated through tunable process parameters, is a demanding process, especially considering the high production rate and voluminous metrics that are collected.

The project considers the design of sketching algorithms, transprecise computing and their efficient implementation on modern high-throughput hardware such as graphics processing units.

RAPID is sponsored by EPSRC.

Project members:

SoftNum: Software-Defined Number Formats

Computing devices implement computer arithmetic as basic functionality, and they implement the same, standardized number formats in order to support software portability. However, with Moore’s Law ending, we question whether it remains the best approach to achieve high performance and low energy consumption by applying the same standardized number formats for all applications. We explore how to make number formats, generally considered to be hard-wired functionality, software-defined. Software-defined number formats have the advantage of high performance, low energy consumption, and ensure sufficient while not excessive precision.

SoftNum is Amir’s individual Marie Sklodowska Curie Fellowship, sponsored by the European Commission.

DiPET: Distributed Stream Processing on Fog and Edge via Transprecise Computing

Publications

The DiPET project investigates models and techniques that enable distributed stream processing applications to seamlessly span and redistribute across fog and edge computing systems.

The goal is to utilize devices dispersed through the network that are geographically closer to users to reduce network latency and to increase the available network bandwidth. However, the network that user devices are connected to is dynamic. For example, mobile devices connect to different base stations as they roam, and fog devices may be intermittently unavailable for computing.

In order to maximally leverage the heterogeneous compute and network resources present in these dynamic networks, the DiPET project pursues a bold approach based on transprecise computing.

Transprecise computing states that computation need not always be exact and proposes a disciplined trade-off of precision against accuracy, which impacts on computational effort, energy efficiency, memory usage and communication bandwidth and latency. Transprecise computing allows to dynamically adapt the precision of computation depending on the context and available resources.

This creates new dimensions to the problem of scheduling distributed stream applications in fog and edge computing environments and will lead to schedules with superior performance, energy efficiency and user experience.

The DiPET project will demonstrate the feasibility of this unique approach by developing a transprecise stream processing application framework and transprecision-aware middleware. Use cases in video analytics and network intrusion detection will guide the research and underpin technology demonstrators.

Please refer to the website for the details of the project: https://dipet.eeecs.qub.ac.uk

This project is sponsored by CHIST-ERA and EPSRC.