Dedicated links from your HQ, R&D centres, plants and cloud to the AI computing centre, supercomputing centre or GPU cloud you choose. Guaranteed bandwidth, predictable latency and no public internet — with circuits, data-centre cross-connects, acceleration and operations handled by GSS, so your team can focus on models and the business.
More and more companies rent GPU capacity instead of building their own. The hard part is usually not the compute but getting data and applications there safely and quickly: carrier circuits, cross-connects inside the compute centre, bandwidth planning, acceleration, security and operations.
AI & Supercomputing Connect packages all of that into one service. Tell us which compute centre and how much bandwidth; GSS delivers and runs the whole path from your sites to the compute centre's data hall.
Your sites connect to the GSS network once; we deliver and run the links, cross-connects, acceleration and security to every compute centre.
Tell us the compute centre and bandwidth. Survey, carrier selection, cross-connects and testing are on us.
Dedicated bandwidth plus transfer acceleration turns overnight dataset transfers into hours.
Private circuits with encryption and access control; cross-border transfers are logged by an audit gateway.
Connect several compute centres on one network and switch or scale without new cabling.
With the GSS AI API gateway, hosted models are called like internal services, with quotas and cost by department.
24×7 NOC watches circuits and latency to each compute centre, with 15-minute P1 response and monthly reports.
| Scenario | How it connects | Best for |
|---|---|---|
| Training data sync | Data room / storage ↔ AI computing centre; dedicated line + acceleration | Regular bulk uploads and model downloads |
| R&D on supercomputers | R&D centre ↔ supercomputing centre; private line or MPLS VPN | Simulation, CAE, drug discovery |
| Central inference | Plants / stores / campuses → SD-WAN → inference cluster | Inspection, customer service, video analytics |
| Multiple compute centres | One SD-WAN / MPLS network to several providers | Price comparison, elastic capacity, resilience |
| Cross-border compute | Shanghai / Beijing ↔ Singapore / Tokyo / Hong Kong / Los Angeles | GPU clusters abroad, with transfer audit |
Which compute centres, how much data, latency targets and security boundary; bandwidth and cost estimate.
Carrier and route selection, cross-connects, dual paths and acceleration.
Local loop, cross-connects and equipment; end-to-end throughput and latency tests.
24×7 NOC; bandwidth adjusted to training and inference load; new compute centres join the same network.
Moving 40 TB daily datasets from Shanghai to GPU clusters in Singapore and Tokyo took 20+ hours over the internet, and training data had to leave China over an auditable path.
MPLS between plants was costly and slow to scale, cloud ERP/MES performed poorly, and the nightly data sync with the German HQ took more than six hours.
Every store ran on a single broadband line; POS and loyalty systems dropped at peak hours. Customer data could not leave the company boundary.
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