Axiotech Hyperion X-Series
HPC, CUDA and AI engineering guidance from first principles to production deployment—mapped to real industrial, research and academic workloads.
Use the foundations to plan architecture and software; sector guides to map a field; application notes to implement a specialised workflow; and product briefs to select and validate a Hyperion baseline. Performance figures are intentionally workload-led: final systems are sized from representative code, data, concurrency and operating requirements.
Applications and industries
Memory-bound assembly and variant pipelines in research and sequencing-core production, with imaging AI beside the instrument.
Research computing inside the hospital network and clinical AI assistants that keep patient data on site.
From discovery model development to validated production pipelines over confidential compound and trial data.
CFD, FEA and design-of-experiments in production, with surrogate-model AI trained from simulation output.
Sovereign AI behind your firewall: serving fleets, large-model tiers and organisation-scale platforms with hybrid cloud gateways.
Build farms, CI matrices and developer AI on production-class silicon: compile in minutes, test in containers and serve assistants from your own rack.
PLC and motion software development with automated validation, virtual commissioning, digital twins and an LLM assistant that never sees outside the plant network.
Factory management systems with AI in production: line monitoring, vision inspection, predictive maintenance and shift-level analytics.
Perception for machines that move: inspection, pick-point models, robot-cell simulation and low-latency serving beside the line.
MATLAB, R, Julia and Python at 96–128 cores, whole datasets in memory, and Monte Carlo or optimisation runs that finish over lunch instead of overnight.
Complete library
HPC & AI foundation
How to turn departmental HPC and AI hardware into a sustainable research and teaching service with fair access, reproducible environments and publishable evidence.
Technical sector guide
MATLAB, R, Julia and Python at 96–128 cores, whole datasets in memory, and Monte Carlo or optimisation runs that finish over lunch instead of overnight.
Application note
A secure runner design for CPU compilation, accelerator smoke tests, numerical regression and scheduled performance gates.
Application note
Run validated physics at scale, then train bounded surrogate models to screen designs and shorten engineering iteration.
Application note
A campaign design joining CPU preparation, GPU simulation, biomolecular models, scheduler arrays and governed scientific evidence.
Application note
Choose threads, processes, MPI or CUDA by algorithm; preserve random streams and report efficiency, uncertainty and completed scenarios.
Application note
A shadow-mode-to-production architecture for DICOM routing, MONAI inference, clinical-format outputs, audit and rollback.
Application note
Build a governed feature and inference pipeline that combines machine state, maintenance outcomes and visual evidence without flooding operators with alarms.
Application note
A reproducible Nextflow/Slurm pattern for sample throughput, memory-heavy assembly, accelerated stages and governed genomic data.
Application note
A closed-loop workflow from calibrated data and simulation through GPU training to bounded, low-latency perception beside the robot cell.
Application note
Permission-aware retrieval, efficient inference, evaluation, monitoring and controlled hybrid routing for confidential enterprise knowledge.
Application note
Automate TwinCAT project builds, simulate machine sequences and use locally hosted AI without crossing the real-time or safety boundary.
HPC & AI foundation
A workload-first method for selecting cores, memory capacity and bandwidth, accelerator topology, NVMe, shared storage and RDMA across the Hyperion X-Series.
Technical sector guide
Sovereign AI behind your firewall: serving fleets, large-model tiers and organisation-scale platforms with hybrid cloud gateways.
Technical sector guide
Memory-bound assembly and variant pipelines in research and sequencing-core production, with imaging AI beside the instrument.
Technical sector guide
From discovery model development to validated production pipelines over confidential compound and trial data.
Technical sector guide
Perception for machines that move: inspection, pick-point models, robot-cell simulation and low-latency serving beside the line.
Technical sector guide
PLC and motion software development with automated validation, virtual commissioning, digital twins and an LLM assistant that never sees outside the plant network.
Technical sector guide
CFD, FEA and design-of-experiments in production, with surrogate-model AI trained from simulation output.
Technical sector guide
Build farms, CI matrices and developer AI on production-class silicon: compile in minutes, test in containers and serve assistants from your own rack.
Technical sector guide
Research computing inside the hospital network and clinical AI assistants that keep patient data on site.
HPC & AI foundation
An operations blueprint for schedulers, GPU allocation, identity, quotas, fabrics, monitoring, backups and controlled change on multi-user Hyperion systems.
Product use brief
A professional development and proof-of-concept node for CUDA, AI, data science and software engineering.
Product use brief
A CPU- and memory-led HPC platform for simulation, genomics, analytics, compilation and workloads with large in-memory working sets.
Product use brief
A controls-engineering and virtual-commissioning platform for TwinCAT, PLC, motion, simulation and private engineering AI.
Product use brief
A large-memory single-GPU platform for private LLM inference, retrieval-augmented generation, medical imaging and large scientific models.
Product use brief
A production-intelligence node for machine vision, telemetry, predictive maintenance and low-latency factory AI.
Product use brief
A professional two-GPU training, visualisation and applied-research server for larger datasets and models.
Product use brief
A dense inference, RAG, CI and multi-service node where several independent GPU workloads must run concurrently.
Product use brief
The maximum single-node Hyperion platform for AI training, molecular modelling, generative engineering and large accelerated workflows.
Product use brief
A tightly coupled two-node simulation and mathematical-computing platform for MPI, CFD, FEA and optimisation.
Product use brief
A two-node multi-user AI workgroup for clinical research, production intelligence, training and resilient service placement.
Product use brief
A shared departmental CPU-compute facility for research pipelines, simulation, genomics and queued multi-user work.
Product use brief
A sustained departmental AI/HPC platform for pharmaceutical modelling, large training campaigns and shared accelerated research.
Product use brief
The flagship sovereign AI and research-computing platform for organisation-scale shared services and the largest Hyperion workloads.
Technical sector guide
Factory management systems with AI in production: line monitoring, vision inspection, predictive maintenance and shift-level analytics.
HPC & AI foundation
A practical software-engineering system for repeatable builds, traceable datasets, benchmark gates and portable execution across workstations, servers and clusters.
HPC & AI foundation
Drivers, CUDA, frameworks, collectives, containers, inference servers and schedulers arranged as an operable stack rather than an accidental collection of packages.
Workload review
Bring Axiotech a representative workload, dataset, software stack, concurrency target and site constraints. We will map them to a Hyperion baseline and formal quotation.