AI & Machine Learning Servers
Training large language models, running inference workloads, or building your first GPU cluster demands hardware that can sustain extreme parallel computation around the clock. ICD supplies purpose-built AI server platforms from Dell, HPE, and Lenovo, pre-validated with NVIDIA GPUs and high-bandwidth memory — so your data science team spends time on models, not on hardware troubleshooting. Every configuration is verified for compatibility before it ships.
AI and machine learning workloads are fundamentally different from traditional enterprise computing. They require massive parallel processing power from GPUs, ultra-fast data pipelines through NVMe storage, and enough system memory to stage large datasets without bottlenecks. Whether you are fine-tuning a foundation model, running real-time inference at the edge, or scaling a multi-node training cluster, the underlying hardware choices determine your time-to-result and cost-per-token.
ICD provides the full stack: GPU-ready server chassis, NVIDIA accelerators (A100, H100, L40S), high-capacity DDR5 RDIMM kits, and PCIe Gen5 NVMe drives — all sourced as genuine OEM parts with verified cross-compatibility.
Recommended specifications
| Component | Minimum | Recommended | Notes |
|---|---|---|---|
| CPU | Dual Intel Xeon Gold 6330 (56 cores total) | Dual Intel Xeon Gold 6448Y or AMD EPYC 9454 (96+ cores total) | CPU feeds data to GPUs — insufficient cores create a bottleneck during preprocessing |
| RAM | 256 GB DDR4-3200 RDIMM | 512 GB – 1 TB DDR5-4800 RDIMM | Large datasets must fit in memory for efficient GPU feeding; DDR5 doubles bandwidth |
| GPU | 2x NVIDIA A30 (24 GB HBM2 each) | 4-8x NVIDIA H100 SXM5 (80 GB HBM3 each) or L40S for inference | H100 delivers 3x training throughput over A100; L40S is cost-effective for inference |
| Storage | 2x 1.92 TB NVMe SSD (RAID 1 for OS) + 4x 3.84 TB NVMe | 8x 3.84 TB PCIe Gen5 NVMe in RAID 0/10 for dataset staging | NVMe eliminates the storage I/O wall; Gen5 doubles throughput vs Gen4 |
| Network | Dual 25GbE SFP28 | Dual 100GbE QSFP28 or InfiniBand HDR (200 Gb/s) | Multi-node training requires ultra-low-latency GPU-to-GPU communication |
| RAID / Storage Controller | Onboard NVMe passthrough (no HW RAID needed for NVMe) | Dell BOSS-S2 for OS mirror + NVMe direct-attach for data | Hardware RAID adds latency for NVMe; use software-defined or direct attach |
Recommended servers
Compatible parts
Why ICD?
Compatibility Checked
Every GPU-to-server combination validated against OEM compatibility matrices — no surprise POST failures
500,000+ Genuine Parts
Including hard-to-find NVIDIA accelerators and InfiniBand HCAs from 120 brands
AI-Specialized Engineers
Engineers who understand GPU topology, NVLink, PCIe lane allocation, and thermal envelopes
Global Delivery
Ships to Egypt, KSA, UAE, and 100+ countries with tracked express delivery
Ready to Build Your AI Infrastructure?
Get a custom configuration designed for your workload — training, inference, or hybrid.