End-to-End AI Compute Infrastructure Deployment Solution

From Core Logic to High-Performance Computing Hardware

Implementation Roadmap
01

Requirement Discovery

Build a precise compute assessment plan based on model scale and expected concurrency.

02

Solution Customization

Design topology architecture with NVLink and InfiniBand high-speed interconnect planning.

03

Hardware Delivery

Complete efficient full-system burn-in testing and high-quality hardware delivery.

04

Environment Deployment

Pre-install CUDA and PyTorch environments for an out-of-the-box development experience.

05

Continuous Optimization

Perform deep VRAM and inference optimization for Llama and DeepSeek-class workloads.

Server Specifications
Computing Unit Topology Target Task
NVIDIA H100 8-GPU Cluster 900GB/s NVLink 4.0 Ultra-large LLM training / 100B+ parameter inference
NVIDIA H200 Liquid Cooling 600GB/s NVLink 3.0 Research parallel computing / industrial-scale vision workloads
NVIDIA RTX 5090 Hybrid Cluster PCIe Gen5 + optional NVLink bridge + 400G RoCE networking Cost-efficient fine-tuning / multimodal inference / AI rendering pipelines
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One-Stop Delivery Scope

From requirement discovery to production rollout, we provide integrated delivery across architecture, hardware, software environment, and operations.

Typical Deployment Scenarios

  • Large-scale model training and fine-tuning clusters
  • Enterprise private AI inference platforms
  • Multimodal content generation and rendering pipelines

Service Commitment

  • Fast hardware provisioning and acceptance validation
  • 24/7 technical response and operational support
  • Continuous cost/performance optimization planning