Everything you need to know about NVIDIA H100 PCIe

Interface: PCIe Gen 5.0 x16
Power Consumption: Up to 350W for the 80GB variant, up to 700W for the 96GB variant.
Memory: 80GB HBM2e (or up to 96GB HBM3 in some models).
Memory Bandwidth: 2.04 TB/s for the 80GB variant, up to 1.68 TB/s for the 96GB variant.
Cooling Design: Dual-slot active cooling.
Form Factor: PCIe, designed for broad compatibility with standard server infrastructures.
Architecture: NVIDIA Hopper.
Compatibility: Compatible with standard PCIe slots, making it suitable for a wide range of server environments.
Compute Cores: 14,592 CUDA cores (80GB variant) or 16,896 CUDA cores (96GB variant), and 456 Tensor cores (80GB variant).
Compute Performance: Up to 51.22 TFLOPS of FP32 and 1000 TFLOPS of FP8 performance.
MIG Technology: Supports partitioning into up to seven independent instances for optimized resource utilization.
Special Features: Includes a dedicated Transformer Engine for accelerating large AI models.
Confidential Computing: Ensures data remains encrypted during processing.

AI and Deep Learning: The H100 PCIe accelerates training and inference of large AI models like GPT-3, significantly speeding up processes and reducing deployment time.
High-Performance Computing (HPC): It excels in tasks like genomic sequencing, climate modeling, and scientific simulations due to its high computational power and memory bandwidth.
Data Analytics: The H100 PCIe supports real-time processing of large datasets, crucial for industries needing timely data-driven decisions.
Enterprise AI Workloads: Bundled with the NVIDIA AI Enterprise suite, it streamlines the development and deployment of AI workflows, integrating advanced AI into existing systems.

Cooling and Power: Ensure your server can support the H100 PCIe's 350W to 700W power needs and active cooling, especially in dense deployments.
Infrastructure Compatibility: The PCIe Gen 5.0 interface integrates smoothly into existing systems, but confirm your infrastructure can handle its high bandwidth and power demands.
Software Optimization: Utilize NVIDIA AI Enterprise, CUDA, cuDNN, and TensorRT to optimize workloads, leveraging the H100's advanced Tensor Cores and Transformer Engine.
Scalability: Use NVIDIA NVLink to connect multiple H100 PCIe GPUs for scalable, low-latency setups, ideal for large AI models and complex simulations.

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