Research & higher education
Shared computing for teaching, research groups, simulation, scientific Python, reproducible environments and data analysis.
Explore scientific computingINDUSTRY APPLICATIONS
HPC and AI use cases across industries
Explore common workload patterns for research, engineering and data-intensive teams. These are industry reference examples, not MCR Tech customer deployments. Workload fit depends on the selected software, data, hardware and operating requirements.
WORKLOAD AREAS
Start with the application and data pattern
Each example links to a related directory search or guide. It is an orientation aid, not a guaranteed hardware recommendation.
Life sciences & healthcare research
Bioinformatics, molecular modelling, imaging research and AI-assisted scientific workflows, subject to data governance and application validation.
Search bioinformatics applicationsManufacturing & engineering
CFD, FEA, computational engineering, design exploration, numerical analysis and technical visualisation.
Search simulation softwareEnergy & geoscience
Reservoir and geospatial analysis, numerical modelling, seismic workflows and large scientific datasets.
Search related applicationsWeather, climate & environment
Forecasting research, climate simulation, environmental modelling and long-running batch workloads.
Search weather and climate toolsAI & data platforms
Model development, inference, evaluation, computer vision, retrieval workflows and data engineering.
Explore AI infrastructure softwareGovernment, public sector & research
Shared research platforms and data services planned around procurement, access, governance, security and documented operating responsibilities.
Explore HPC softwareMedia, video & visual computing
Video processing and visual-computing pipelines sized for codec, resolution, frame rate, stream concurrency, models and latency targets.
Search video applicationsFinance, risk & analytics
Data analysis, risk modelling, simulation and model evaluation subject to data handling, software licensing and governance requirements.
Search analytics applicationsLearning & skills development
Published learning resources can cover Linux, containers, Kubernetes, Slurm, GPU systems, storage, networking and scientific workflows.
Review published coursesINDUSTRY TO WORKLOAD MAPPING
Translate a sector need into a system question
| Industry area | Example workload family | Planning questions | Related starting point |
|---|---|---|---|
| Research & education | Simulation, teaching, scientific Python, batch jobs | How many users run jobs at once? Which applications and versions must be supported? | Scientific computing |
| Life sciences | Bioinformatics, molecular modelling, imaging | What data governance, storage lifecycle and software licensing apply? | Application search |
| Engineering | CFD, FEA, optimisation, visualisation | Is the solver CPU, GPU or MPI accelerated? What benchmarks and precision are required? | Application search |
| Energy & climate | Geospatial analysis, forecasting, numerical simulation | What are the data volumes, I/O pattern, job duration and turnaround target? | Application search |
| Media & enterprise AI | Video inference, model serving, analytics | Which codecs, request rates, concurrency, model formats and response times matter? | GPU guide |
The mapping describes example questions, not a commitment to a specific product, deployment or performance result.
PLAN A WORKLOAD REVIEW
Choose software with the full environment in view
Share the application, versions, data profile, users, current systems and constraints. The team can review an appropriate next step and scope separately.