While not a physical component, the software stack—including operating systems, ML frameworks, containerization, and orchestration tools—is critical for performance. Networking hardware, such as high-speed interconnects, ensures efficient data movement between GPUs and storage. These layers are essential for AI workloads but are not typically quantified in physical proportion terms .
| Component | Approximate Proportion of Value |
|---|---|
| GPU Board Assembly | 50–60% |
| CPU Motherboard Assembly | 20–25% |
| Memory (HBM/DRAM) | 10–15% |
| Storage (NVMe/SSD) | 5–10% |
| Power & Cooling | 5–10% |
| Semiconductors (overall) | >50% of total server rack cost |
This distribution emphasizes that GPUs and semiconductors dominate both the computational capability and cost structure of AI servers, while CPUs, memory, storage, and power/cooling support the high-performance AI workloads .
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