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AI infrastructure: GPU systems and cooling for AI
GPU systems for training, inference and private AI, scoped with the interconnect, memory and cooling each workload needs. The systems and the cooling can be covered by one written quote.
01
What it is
AI capacity needs GPU systems that match what was specified, arrive when agreed, and come with paperwork that stands up to scrutiny.
We confirm the requirement, check it against power, cooling and interconnect, source it from reputable channels, carry out the compliance checks that a careful supplier should, and put the whole thing in a written quote before anyone commits.
02
Who it is for
- AI training clusters, where many GPUs work as one.
- Inference and edge, with smaller footprints, predictable latency and often many sites rather than one.
- Enterprise private AI, where data cannot leave the building.
- Businesses, resellers and integrators, public sector bodies, and research or education organisations. We do not take enquiries from consumers.
03
AI training clusters
Training runs want many GPUs working as one. The hard part is rarely the GPU itself; it is the fabric between nodes, the memory per node, and whether the facility can power and cool a full rack.
We scope the cluster as a whole, from node configuration to switching and cabling, and quote it in writing with the site constraints written down.
What buyers usually need
- GPU class: multi GPU rack servers or rack scale systems.
- Interconnect: high speed fabric between nodes.
- Memory: large host memory per node.
- Storage: fast shared storage for data and checkpoints.
Cooling to consider
Dense training racks usually need liquid at the chip, with a CDU in the rack or row. Direct-to-chip, CDUs.
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04
Inference and edge
Serving models in production is a different shape of problem: smaller footprints, predictable latency and often many sites rather than one.
We help you size per site systems and quote repeatable configurations, so each location gets the same build.
What buyers usually need
- GPU class: smaller GPU servers or PCIe GPUs in standard hosts.
- Interconnect: standard Ethernet in most cases.
- Memory: sized to the models served.
- Storage: local, for models and logs.
Cooling to consider
Usually air cooled. A rear door heat exchanger can help where several nodes share a small room. Rear door heat exchangers.
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05
Enterprise private AI
Some data cannot leave the building. Private AI capacity means GPU systems on your own premises, sized to the workload and fitted into an existing estate.
We scope against your current racks, network and security requirements, and quote systems that fit what you already run.
What buyers usually need
- GPU class: GPU servers, sometimes a small rack scale system.
- Interconnect: Ethernet, with fabric where several nodes train together.
- Memory: matched to the models and fine tuning planned.
- Storage: integrated with existing enterprise storage.
Cooling to consider
Existing comms rooms often favour rear door heat exchangers or liquid-to-air CDUs, because facility water is rare. Rear door heat exchangers, CDUs.
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How we work
Five steps, whether the request is for GPU systems, cooling, or both. Each enquiry carries a reference from receipt, and nothing is agreed until a written quote is accepted.
- 01
Scoping
We confirm workload, configuration, quantity and site constraints before anything else.
- 02
Configuration and validation
We check the bill of materials, power, cooling and interconnect fit before quoting, and check the system against the cooling and power you have or plan.
- 03
Sourcing
We source the configuration and confirm details in the written quote.
- 04
Compliance and checks
Sanctions, export control, end use and know your customer checks before any quote is final.
- 05
Logistics and delivery
We arrange delivery to your site and confirm the terms in writing.
07
Related questions
C02Do GPU servers need liquid cooling?
Not always. Many configurations are available air cooled. Denser nodes and rack scale systems are increasingly designed for liquid, and some are only offered that way. It depends on the configuration; we confirm this in the quote.
Q02What should I include in a quote request?
Your name, work email, company and a short message are enough to start. For a quote, add the platform or system class, quantity range, interconnect, memory per node, timeline, delivery region and end use country under Add project details. Part numbers help.
Q03Can I send a bill of materials or part list?
Yes. Paste it into the Message field. For longer lists, send the form first, then email the file to sales@duvaracompute.com quoting your reference.
Q14Can you quote GPU systems and cooling together?
Yes. That is the point of offering both. Choose "GPU systems and cooling" on the contact form, tell us about the site, and one written quote covers the systems and the cooling equipment. See Cooling.
Q08How do you screen buyers?
We screen the buyer, its owners and the end user against UK sanctions and export control lists before any quote is finalised, and carry out know your customer checks on a first order. A declaration of end use and destination country is required.
Related pages
GPU servers
GPU servers, rack scale GPU systems and PCIe GPUs.
Liquid cooling
Direct-to-chip, CDUs and rear door heat exchangers, for dense racks.
HPC
Research labs, engineering and simulation, data centres and colocation.
Colocation
Colocation space in mainland UK and Europe, sourced with your systems.
Request a quote
Ask a question or request a quote for GPU systems, cooling, or both. We reply to enquiries as soon as we can.