High-performance, cloud and edge computing
High-performance, cloud and edge computing provide the processing and storage capacity for simulation, analytics and digital services. They are both an enabler of risk analysis and a critical dependency for society. Data and Compute stewards this page for the Nexus Consortium.
- 01In briefThe short answer
- 02The methodWhat high-performance, cloud and edge computing covers
- 03Reference practiceComputing practice is measured by performance, efficiency and reproducibility
- 04In systemic risk workCompute sets the resolution of what can be known
- 05Applied inPlatforms that apply this method
- 06StewardshipWho maintains this page
- 07Key termsTerms used on this page
GCRI · Institution · service level R0
The short answer.
High-performance, cloud and edge computing provide the processing and storage capacity for simulation, analytics and digital services. Computing capacity determines how fast and at what resolution risks can be modelled. In the Nexus Consortium, Data and Compute stewards its canonical page, and 7 other platforms apply it, including Nexus Foundry as well as Climate and Hazards.
Systemic exposure in Egypt and the Nile Delta.
Where people and networks concentrate, the exposure through which shocks travel between systems, shown for Egypt and the Nile Delta as an example geography for this subject.
What high-performance, cloud and edge computing covers.
- 01
Core methods
parallel and distributed computing; workload scheduling; virtualisation and containerisation; capacity planning; fault-tolerant system design; performance benchmarking.
- 02
Data and instruments
system performance logs; job scheduler records; energy and cooling telemetry; benchmark results; service availability records.
- 03
Validation
Systems are tested through benchmarks, load testing and failover exercises. Numerical reproducibility is checked across hardware and software configurations.
- 04
Limits
Concentration in few providers or regions creates shared points of failure. Energy, water and supply chain constraints limit capacity growth.
- 05
Use in risk decisions
Computing capacity determines how fast and at what resolution risks can be modelled. Its concentration is itself a systemic dependency for finance, health and government services.
Computing practice is measured by performance, efficiency and reproducibility.
| Reference | What it sets |
|---|---|
| TOP500 and Green500 | Supercomputer performance and energy efficiency rankings |
| ISO/IEC 30134 series | Data-centre efficiency indicators |
| MLCommons benchmarks | Machine-learning performance benchmarks |
Compute sets the resolution of what can be known.
Ensemble size, model resolution and the number of scenarios explored are limited by compute. For systemic risk, compute is also a dependency: public services and science rely on a small number of providers. Reproducibility requires recording the software environment and hardware where results depend on them.
- Record software versions and random seeds.
- Note when results depend on hardware precision.
- Assess continuity of access to compute for critical analysis.
- Applications on Data and Compute and Nexus Foundry.
Platforms that apply this method.
- Nexus FoundryInstitutionGCRI
- Climate and HazardsInstitutionGCRI
- Artificial Intelligence and Autonomous SystemsInstitutionGCRI
- Data and ComputeInstitutionGCRI
- Space and Earth ObservationInstitutionGCRI
- Digital Public InfrastructureInstitutionGCRI
- Systems Science and ModellingInstitutionGCRI
- Actuarial and Quantitative RiskInstitutionGRA
Who maintains this page.
Data and Compute stewards high-performance, cloud and edge computing: it keeps this description current and reviews how the method is applied across the platforms.
Terms used on this page.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Monte Carlo simulation | A method that estimates outcomes by repeated random sampling from probability distributions. |
| End-user computing | Spreadsheets and tools built by business users outside formal software development. |
| High-performance computing | Aggregated computing power, typically clusters with fast interconnects, used for large simulations. |
| Container image digest | A cryptographic identifier of an exact software environment, used to reproduce a run. |
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Where this page leads across the Consortium.
- High-performance, cloud and edge computingGCRIApplied in Nexus Foundry.
- Computing for climate and hazard scienceGCRIApplied in Climate and Hazards.
- Computing for AIGCRIApplied in Artificial Intelligence and Autonomous Systems.
- Computing for public knowledgeGCRIApplied in Data and Compute.
- Computing for Earth observationGCRIApplied in Space and Earth Observation.
- Computing for DPIGCRIApplied in Digital Public Infrastructure.
- Computing for modellingGCRIApplied in Systems Science and Modelling.
- High-performance, cloud and edge computing for actuarial and quantitative riskGRAApplied in Actuarial and Quantitative Risk.
Questions and answers.
Why does one institution host every method page?
How do I suggest a correction to a method page?
Around GCRI.
Start with an enquiry.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.