Supermicro SYS-821GE-TNHR GPU Server Overview: 8 × NVIDIA HGX H100/H200 | Xeon 8570, 2TB DDR5, NVMe

The Supermicro SYS-821GE-TNHR is a purpose-built 8U GPU server designed for large-scale AI training, HPC, and enterprise workloads. At its core, this system supports up to 8× NVIDIA HGX GPUs, including the HGX H100 with 80GB of memory or the HGX H200 with 141GB of memory. Leveraging NVIDIA’s NVLink and NVSwitch technology, the SYS-821GE-TNHR delivers the ultra-high bandwidth and low latency GPU-to-GPU communication required for demanding LLMs, deep learning, and scientific simulations.

For CPU performance, NVIDIA recommends the Intel Xeon Platinum 8570, offering 56 cores and 112 threads in a dual-socket configuration. With support for 4th and 5th Gen Intel Xeon Scalable processors, the system can utilize DDR5 memory speeds up to 5600 MT/s on Emerald Rapids CPUs or up to 4800 MT/s on Sapphire Rapids CPUs. Keep in mind that effective memory speed will clock down depending on CPU generation, DIMM rank, and slot population. NVIDIA’s recommended configuration is 2TB of DDR5 memory, achieved with 32× 64GB ECC Registered DIMMs at 4400 MT/s.

Storage flexibility is another highlight of this server. The SYS-821GE-TNHR supports up to 19× 2.5″ hot-swap bays for NVMe, SAS, or SATA drives, plus 2× M.2 NVMe slots for boot. For enterprise SSDs, you can choose NVMe SSDs at 32Gb/s with capacities up to 30.72TB, SAS SSDs at 24Gb/s up to 15.36TB, or SATA SSDs at 6Gb/s up to 7.68TB. Traditional spinning drives are also supported, with 2.5″ SATA HDDs up to 2TB at 7.2K RPM and 2.5″ SAS HDDs up to 2.4TB at 7.2K, 10K, or 15K RPM.

Altogether, the Supermicro SYS-821GE-TNHR is a GPU-first platform optimized for maximum AI performance, while still offering the flexibility to expand CPU, memory, and storage to match your workloads. Whether you’re training large-scale language models or deploying GPU clusters for enterprise AI, this server provides the reliability and scalability you need.

If you have questions on GPU configurations, CPU selection, or memory population strategies, drop them in the comments below. For quotes, availability, or rail kit options, contact us at [email protected]. Be sure to subscribe for more in-depth server overviews, AI hardware recommendations, and datacenter best practices.

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