Cisco HCI-GPU-H100-80 | H100 80GB PCIe GPU, 350W, HBM3 ECC, MIG-Enabled

Q: What workloads is the H100 PCIe 80GB optimized for?
A: The H100 is designed for large-scale AI model training, LLM inference with trillion-parameter models, high-performance computing, scientific simulations, and data analytics. The Transformer Engine accelerates generative AI workloads, while the 80GB memory capacity supports large datasets and complex neural networks.

Q: How does Multi-Instance GPU (MIG) work on the H100?
A: Second-generation MIG technology allows the H100 to be securely partitioned into up to seven isolated 10GB instances. Each instance operates independently with dedicated compute, memory, and cache resources, enabling multiple users or workloads to share a single GPU while maintaining quality of service and security isolation.

Q: What are the infrastructure requirements for the H100 PCIe?
A: The H100 PCIe requires a PCIe 5.0 x16 slot (backward compatible with PCIe 4.0), 350W power delivery via a 16-pin (12+4) power connector, dual-slot clearance, and adequate airflow as it uses passive cooling. It is compatible with Cisco UCS C-Series and X-Series servers with appropriate PCIe node configurations.

Q: How does the PCIe variant differ from the SXM5 H100?
A: The H100 PCIe uses HBM2e memory with 2TB/s bandwidth and 114 streaming multiprocessors, compared to the SXM5 variant which features HBM3 memory at 3.35TB/s and 132 SMs. The PCIe version has 350W TDP versus 700W for SXM5, and uses standard PCIe interconnect rather than NVLink 4.0 for multi-GPU communication.

Q: What software frameworks are supported?
A: The H100 supports NVIDIA CUDA, cuDNN, TensorRT, PyTorch, TensorFlow, JAX, and other major AI/ML frameworks. It includes Hopper-specific features like the Transformer Engine for FP8 precision, DPX instructions for dynamic programming, and Confidential Computing capabilities for secure workloads on shared infrastructure.