Technology and Digital Systems
The Global Centre for Risk and Innovation (GCRI)
Risk Academy, a Nexortium programmeTechnology and Digital SystemsDepartment of Computing, Data and Quantum Technologies
Cloud and edge systems, high-performance computing, chips and the energy of compute
Data infrastructure, compute and semiconductors covers the computing capacity that science and public services rely on: cloud and edge systems, high-performance computing, the chips they run on, the energy and water compute uses and the pipelines that make results reproducible.
Back to Department of Computing, Data and Quantum Technologies
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Twin figures for West Cornwall: Goonhilly and the Porthcurno cable landings, counted from its layers at their stated dates.
For Data infrastructure, compute and semiconductors: the faculty's twin of the Lizard and Penwith on the planet map, the globe and in 3D. Pick a generator, switch layers, run the instruments; every layer prints its provider and date.
Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and - zoom, 0 resets, V steps through the views, Escape clears.
Flat plan of the same data: relief as contours from the inline grid, the mapped ground infrastructure by kind, the mapped cables and the numbers below. The 3D twin opens on devices with WebGL once its data and library have been checked.
The map loads from this site as it nears the view (MapLibre 6.9.1, checked by hash).
The discipline teaches concentration analysis of providers and regions, power usage effectiveness and water usage effectiveness as the metrics of a facility, reproducible pipelines with provenance records, data sovereignty and rights, and access to research infrastructure. On the twin the data centres and cable landing stations of the Porthcurno valley sit on the terrain under the VIIRS night lights, a proxy for where power is drawn and never a measurement of supply. A graduate can map a service's dependency on providers and landings, estimate the energy and water a workload needs from stated metrics, and audit a pipeline for reproducibility.
This area covers the data infrastructure and computing capacity that science and public services rely on: cloud and edge systems, high-performance computing, chips, the energy and water use of compute, reproducible pipelines and access to research infrastructure. It is taught in the department of Computing, Data and Quantum Technologies, Faculty of Technology and Digital Systems, through 2 courses with it as primary discipline.
8 subtopics, taught across its courses and labs.
Not yet taught by a course: Compute and data infrastructure dependency risk.
Recent developments in data infrastructure, compute and semiconductors, each with its source; sources checked on 16 October 2026. Summaries are short readings of the source; follow the link for the full account.
News and research as they are published, per discipline, with the faculty's other tools.
The newest research, preprints, news and humanitarian reports for Data infrastructure, compute and semiconductors, each with its source and date, load here. Open the research and news hub
From the Academy's risk taxonomy: the discipline's own entries and those of its primary courses, with how many courses teach each.
Courses with this as their primary discipline. Open courses link to the catalogue.
| Lab | What you do in it | Courses using it |
|---|---|---|
| Network lab | Build dependency graphs, find critical nodes, trace cascades | 2 |
| GeoAI lab | Apply Earth observation and machine learning to open imagery | 1 |
Approved for authoringno enrolment and no achievement until authored and reviewed
Nexus Foundry system pages describe what each system and its rooms are designed to do; they are not a service on offer, and studying here gives no access to them.
The catalogue lists each course with its outcomes, labs, hours and level.