UnicoNet Technology Limited · Cloud Reseller Services

Cloud Reseller Services · GPU Compute Cloud

We are a reseller of Microsoft Azure and Amazon AWS global editions and provide technical support. We have also launched a GPU compute cloud service covering AI training, inference and high performance computing scenarios.

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Cloud Services Sections

Microsoft Cloud Azure Global edition cloud products, cloud migration assessment and managed support.
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Amazon Cloud AWS Elastic cloud architecture, migration and deployment, and cost governance.
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NEW GPU Compute Cloud GPU rental, AI training and inference compute power.
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GPU Compute Cloud Services

The GPU compute cloud delivers elastic compute power for workloads that require large-scale parallel processing. Instead of a one-off purchase of expensive GPU hardware, you gain on-demand training and inference capacity.

What We Offer

GPU Instance Rental A range of GPU instance specifications, billed on demand or monthly.	AI Training Clusters Multi-GPU parallel training environments that shorten model training cycles.
Inference Deployment Model rollout, managed inference services and elastic scaling.	Storage and Data High-speed storage and managed datasets, with backup.
Technical Support Environment deployment, driver and framework tuning, and front-line support.	Hybrid Deployment Interconnect on-premises GPU facilities with the cloud for flexible scheduling.

Use Cases

AI Model Training	Deep Learning Inference	3D Rendering and Media
Scientific and Numerical Computing	Genomic and Biomedical Analysis	Big Data Analytics

Powered by NVIDIA data centre-class GPUs (such as the NVIDIA H100 / A100 / L40S series; actual models are subject to supply and the selected solution). Specifications and pricing are subject to a formal quotation and contract.

Integration with Existing Services

The GPU compute cloud can be planned alongside our hardware repair and maintenance, hybrid cloud integration and Azure / AWS reseller services: on-premises GPU facilities connect to the cloud over dedicated lines, critical data stays on site, and cloud compute power can be called on elastically during peak demand.

Service Process

1 · Requirements Assessment (1-2 weeks)
Review compute requirements, model scale and data volume.

2 · Solution Design and Trial (1-3 weeks)
Specify the configuration and validate performance with a PoC.

3 · Deployment and Go-Live
Environment setup, framework tuning and data onboarding.

4 · Monitoring and Support
Continuous monitoring, resource scheduling and technical support.