AMD Instinct MI355X
MI355X system design and integration, including liquid-cooled 8-GPU platforms, ROCm, fabric and storage sizing, and workload acceptance testing.
ONE BALANCED SYSTEM, PROVEN AGAINST THE WORKLOAD.
VENDOR-AGNOSTIC AI INFRASTRUCTURE
Build the whole AI system, not just the GPU rack.
ElioVP designs and integrates compute, scale-up and scale-out networking, storage, software, power and cooling around the workload you need to run.
AMD, NVIDIA or a multi-platform design is selected because the workload and operating constraints support it, never because we are tied to one vendor.
ARCHITECTURE PRINCIPLE
The workload decides the platform.
Vendor agnostic means evaluating each architecture against the same technical and commercial requirements. It does not mean pretending every accelerator, fabric or software ecosystem is interchangeable.
01Workload and model profileTraining, inference, fine-tuning and HPC place different demands on memory, precision, communication, storage and software.
We size the system around the work it must complete.
02Facility envelopeAvailable power, rack density, cooling, floor loading and service access define what can be deployed reliably.
The selected platform must fit the real site, not only a bill of materials.
03Lifecycle economicsUtilization, useful throughput, software maturity, energy, support and expansion paths determine the real cost of output.
Purchase cost is only one input.
04Operations and sovereigntyThe architecture must fit the team that will operate it, the data it will process and the security boundaries it requires.
Those constraints belong in the design from the beginning.
PLATFORM COVERAGE
Current deployments and next-generation planning.
We design for platforms in market today and for rack-scale architectures moving through 2026 partner rollout.
Vendor agnostic is not vendor indifferent. Workload fit, software maturity, facility constraints, service and lifecycle economics decide the architecture, not allegiance to one manufacturer.
NVIDIA B300
DGX B300 and selected OEM HGX B300 systems, with each server’s network, DPU, power, cooling and software configuration validated as part of the complete design.
NVIDIA GB300 NVL72
Liquid-cooled rack-scale integration for the Blackwell Ultra NVLink domain, including facility, fabric, storage, management and operational readiness.
AMD Helios
Architecture and partner-system planning around AMD’s open ORW reference design with MI455X GPUs, EPYC Venice CPUs, AMD Pensando networking and UALink over Ethernet (UALoE).
NVIDIA Vera Rubin
Integration and facility planning for Vera Rubin NVL72 and its compute, networking, storage and software stack as manufacturers scale production and ship partner systems.
Market status reviewed in August 2026. Platform references describe ElioVP engineering, integration and sourcing scope, not local stock or guaranteed delivery dates. Specifications, availability and schedules are confirmed with the selected manufacturer and partner at project start.
FABRIC ARCHITECTURE
Design the network around communication behaviour, not port counts.
The scale-up domain inside a server or rack and the scale-out network across the cluster solve different problems. We engineer both against the workload, topology and failure model.
That includes NVIDIA networking built on the former Mellanox portfolio, as well as open and vendor-specific alternatives where they fit better.
Scale-up domains
AMD Infinity Fabric, NVIDIA NVLink and NVSwitch, and UALink technologies are evaluated within their platform-specific domains.
NVIDIA networking
Quantum InfiniBand, Spectrum-X Ethernet, ConnectX adapters and BlueField DPUs are planned as part of the complete data path.
InfiniBand
A strong option when predictable latency, collective communication and mature HPC or large-scale AI operations justify a dedicated fabric.
Ethernet and RoCE
NVIDIA Spectrum-X and AMD Pensando are evaluated alongside standards-based Ethernet designs. Multi-vendor choice depends on validated interoperability, congestion control, telemetry and lossless behaviour.
THE SURROUNDING SYSTEM
Usable GPU capacity depends on everything around it.
Accelerators only create value when data can reach them, software can schedule them and operators can keep the full platform healthy.
Storage and data paths
NVMe, parallel file, object and capacity tiers matched to ingest, checkpoint, model loading, preprocessing and inference flows.
Software and orchestration
ROCm or CUDA, drivers, firmware, containers, Slurm, Kubernetes, model serving, scheduling and observability validated together.
Security and operations
Management networks, access boundaries, firmware policy, logging, monitoring and multi-tenancy aligned to the deployment risk profile.
ACCEPTANCE AND VALIDATION
Prove the system before production depends on it.
A delivered rack is not the same as a production-ready AI platform. We define acceptance criteria before procurement and verify the integrated system against them.
01Design validationConfirm the bill of materials, topology, failure domains, capacity assumptions, facility fit and software compatibility.
Resolve incompatible assumptions before orders are locked.
02Platform acceptanceValidate firmware consistency, hardware health, burn-in, collective communication, storage throughput, fabric behaviour, power and thermal operation.
The acceptance plan follows the actual architecture.
03Workload proof and handoverRun representative workloads against an agreed baseline, document the configuration and set operating thresholds.
The customer team receives the procedures and evidence needed to take over.
CONNECTED BY DESIGN
Start with the cluster or the facility around it.
AI Infrastructure can be deployed in an existing data center, a colocation environment or a new ModFlex facility.
ModFlex creates the physical environment. ElioVP AI Infrastructure creates and validates the productive system inside it. Start with either layer, or engineer both against one power, cooling, performance and resilience model.
Start with the workload, power envelope and operating target.
Share what you need to run, where it must operate and how you will measure success. ElioVP will map the compute, fabric, storage, software and validation path around it.