Outputs (463)

Pickcells: A physically reconfigurable cell-composed touchscreen (2019)
Presentation / Conference Contribution

Touchscreens are the predominant medium for interactions with digital services; however, their current fixed form factor narrows the scope for rich physical interactions by limiting interaction possibilities to a single, planar surface. In this paper... Read More about Pickcells: A physically reconfigurable cell-composed touchscreen.

A streaming dataflow engine for sparse matrix-vector multiplication using high-level synthesis (2019)
Journal Article

Using high-level synthesis techniques, this paper proposes an adaptable high-performance streaming dataflow engine for sparse matrix dense vector multiplication (SpMV) suitable for embedded FPGAs. As the SpMV is a memory-bound algorithm, this engine... Read More about A streaming dataflow engine for sparse matrix-vector multiplication using high-level synthesis.

Composing with Crystallography (2019)
Journal Article

In 2016, I started a collaborative project with Architects and Crystallographers from Cardiff University to explore creative opportunities within crystallographic data-sets and modelling algorithms. This composition research developed and extended th... Read More about Composing with Crystallography.

Pipelined streaming computation of histogram in FPGA OpenCL (2018)
Presentation / Conference Contribution

The emergence of High-Level Synthesis (HLS) techniques and tools, along with new features in high-end FPGAs such as multi-port memory interfaces, has enabled designers to utilize FPGAs not only for compute-bound but also for memory-bound tasks. This... Read More about Pipelined streaming computation of histogram in FPGA OpenCL.

Nucleic Acid Analysis 4 (2018)
Digital Artefact

7 pieces of synthesised music, often with beats.

Adaptive partitioning using partial replication for sensor data (2018)
Presentation / Conference Contribution

There is a huge increase in IoT network size and applications. It has increased the amount of the IoT data that needs to be handled by the applications. State-of-the art workload based static partitioning methods scale poorly and often result in poor... Read More about Adaptive partitioning using partial replication for sensor data.

A liquid tangible display for mobile colour mixing (2018)
Presentation / Conference Contribution

Digital painting is an increasingly popular medium of expression for many artists, yet when compared to its traditional equivalents of physical brushes and viscous paint it lacks a dimension of tangibility. We conducted observations and interviews wi... Read More about A liquid tangible display for mobile colour mixing.

Development of machine learning models to predict student performance in computer literacy courses (2018)
Journal Article

This paper reports on a study carried out to build machine learning models for the purpose of predicting student performance in a second course of a two-course sequence, based on performance in various aspects of the first course’s exam. Detailed dat... Read More about Development of machine learning models to predict student performance in computer literacy courses.

Dynamic energy management of FPGA accelerators in embedded systems (2018)
Journal Article

In this article, we investigate how to utilise an Field-Programmable Gate Array (FPGA) in an embedded system to save energy. For this purpose, we study the energy efficiency of a hybrid FPGA-CPU device that can switch task execution between hardware... Read More about Dynamic energy management of FPGA accelerators in embedded systems.

ML-Aided simulation: A conceptual framework for integrating simulation models with machine learning (2018)
Presentation / Conference Contribution

Recent trends towards data-driven methods may require a substantial rethinking regarding the practice of Modeling &Simulation (M&S). Machine Learning (ML) is now becoming an instrumental artefact for developing new insights, or improving already esta... Read More about ML-Aided simulation: A conceptual framework for integrating simulation models with machine learning.