Distributed Training
Model parallelism, collective communication bandwidth, checkpoint persistence, and target time-to-train.
WORKLOAD → SYSTEM REQUIREMENTS → OPERATING BOUNDARY → SUPPLY
GPU Workload Sizing · UAE
Workload first.
GPU second.
Describe your workload. We structure requirements across compute, fabric, storage, software, access, and facility interfaces.
Specific GPU configuration, availability, operating model, term, and pricing are confirmed separately.
AHQ / WORKLOAD COMPILERREQUIREMENTS MODEL · REV 01
SELECT A LAYER
TO RECOMPILE THE SYSTEM
TO RECOMPILE THE SYSTEM
ACTIVE LAYER · WORKLOAD OBJECTIVEOUTPUT · PARAMETER PROFILE
Compute ProfileAccelerator balance & memory
Interconnect FabricNetwork topology & throughput
Storage I/OThroughput & checkpoint rate
Operating BoundaryTenancy, access & security scope
Workload Archetypes
GPU count alone does not determine the system outcome.
The same accelerator count can produce different outcomes depending on fabric, storage I/O, software, and the operating boundary.
Production Inference
Memory footprint, context length, concurrency, dynamic batching, KV cache budgeting, and latency targets.
HPC & Simulation
CPU-to-GPU balance, MPI communication patterns, system/GPU memory bandwidth, and sustained scratch I/O.
System sizing models requirements causality; it does not constitute a generic benchmark guarantee.
Parameter Translation
System architecture begins with workload parameters.
We map your specific training, inference, or simulation requirements into structured hardware and software specifications.
Training Inputs
Model architecture, precision, dataset volume, batch size, parallelism scheme, and checkpoint frequency.
Inference Inputs
Model, context window, concurrency level, throughput and latency targets, KV cache, and availability requirements.
HPC & Simulation Inputs
Solver application, CPU/GPU balance, MPI communication profile, memory bandwidth, and scratch I/O pattern.
Unspecified parameters are marked as assumptions requiring validation during detailed engineering review.
System Requirements
From workload objective to system requirements.
Sizing translates workload objectives into a unified system specification across all infrastructure layers.
The 6-Layer Architecture Spine
1. Workload Objective:
Target completion time or throughput baseline.
2. Compute Profile:
Accelerator class, count & host system resources.
3. Fabric Requirements:
Interconnect type, bandwidth & cluster topology.
4. Storage Profile:
Usable capacity, sustained throughput & checkpoint I/O.
5. Software & Access:
Environment, container platform & workload scheduler.
6. Facility Interface:
Power, cooling, network and physical deployment requirements.
Operations & Governance
Define the operating boundary that matches your team.
Infrastructure operations extend far below the compute layer. We help determine which stack layers your team manages and which require external operation.
These are target operating boundaries, not available service tiers. Actual responsibilities are confirmed only after the contractual chain is defined.
- Access Models
- Bare metal · Scheduler · Kubernetes · Managed API
- System Layers
- Facility · Firmware · Fabric · Storage · Monitoring
- Operational Functions
- Spares · RMA · Incidents · Data lifecycle
- Responsibility Actors
- Client · Proposed operator · Facility · OEM
- Boundary Status
- TO DEFINE across operational stack
- Contractual Model
- Confirmed separately per engagement
Supply & Capacity Verification
Required system and available supply are separate stages.
Qualification defines what the workload requires. Supply confirmation determines what can be provided under the required technical and commercial conditions.
What the Workload Requires
Required compute profile, fabric topology, storage I/O, software stack, access boundary, and facility requirements.
What Can Be Supplied
Open confirmations: hardware availability, vendor lead time, deployment schedule, SLA terms, and pricing.
BOUNDARY REGISTER / OPEN
Define what must be reserved — and what may remain shared.
Reservation is not a GPU count or a product tier. It is an explicit decision across technical, operational, and contractual layers.
- 01 Resource scope Which compute, fabric, and storage resources require exclusive allocation? Sizing input
- 02 Shared layers What may remain shared without violating performance, security, or data constraints? Operating model
- 03 Substitution rule Which changes in accelerator, topology, or component vendor would remain acceptable? Client decision
- 04 Commercial envelope What term, minimum commitment, and billing basis would apply? Supplier confirmation
- 05 Lifecycle & exit How would maintenance, replacement, incident handling, and data termination be governed? Contract confirmation
No capacity is implied by this register. Reservation exists only after architecture, supply, operating boundaries, and commercial terms are confirmed.
Start Technical Intake
Describe your workload — begin with requirements, not a static catalog.
Select your workload archetype. You can begin qualification with partial parameters; missing specifications will be evaluated during the sizing review.