Technical Details - NVIDIA DGX H100
Interface: The DGX H100 system integrates eight NVIDIA H100 Tensor Core GPUs, all connected using NVLink and NVSwitch, providing 900 GB/s of bidirectional bandwidth between GPUs.
Power Consumption: The system operates with a power requirement of up to 10 kW, making it ideal for large-scale AI and high-performance computing (HPC) environments.
Memory: Each GPU is equipped with 80GB of HBM3 memory, offering a total of 640GB across the entire system, designed for large datasets and memory-intensive applications.
Memory Bandwidth: The DGX H100 delivers 3.35 TB/s of memory bandwidth per GPU, with a total bandwidth of 26.8 TB/s across the system, ensuring fast data access and efficient model processing.
Cooling Design: The system employs a combination of air and liquid cooling, optimized for dense data center setups to maintain ideal performance under heavy loads.
Form Factor: The DGX H100 is housed in a 4U rack-mountable chassis, making it compatible with standard server racks for easy integration in enterprise environments.
Architecture: Built on NVIDIA’s Hopper architecture, the system features Tensor Core and Transformer Engine technology, optimized for next-gen AI workloads such as large language models (LLMs) and generative AI.
Compute Performance: The system can deliver up to 3,341 TFLOPS in FP8 precision, positioning it as one of the fastest computing platforms for AI and HPC tasks.
MIG Technology: The Multi-Instance GPU (MIG) feature allows each H100 GPU to be partitioned into seven instances, enabling flexible and scalable resource allocation for multiple workloads.
Special Features: Bundled with NVIDIA AI Enterprise, this system provides a complete software stack for seamless AI model deployment and management.
Applications and Implementations - NVIDIA DGX H100
AI and Deep Learning: Specifically designed for training and inference of large models like GPT-3 and LLaMA-2, the DGX H100 provides up to 6x faster performance compared to previous systems, making it ideal for enterprise-level AI.
High-Performance Computing (HPC): The system is capable of running complex scientific simulations, thanks to its enhanced memory bandwidth and compute performance.
Data Analytics: With 640GB of HBM3 memory and 400Gb/s network interfaces, the DGX H100 excels in real-time analytics and handling massive datasets efficiently.
Enterprise AI Workloads: Integrated with NVIDIA AI Enterprise, the DGX H100 is tailored for large-scale deployments in industries such as finance, healthcare, and autonomous systems.
Practical Tips for Implementations - NVIDIA DGX H100
Cooling and Power: Ensure your data center can handle the 10 kW power requirement and has an advanced cooling infrastructure to support continuous, high-performance operation.
Infrastructure Compatibility: Leverage PCIe Gen 5.0, NVLink, and 400Gb/s networking for optimal performance and scalability in AI and HPC environments.
Software Optimization: Maximize the system’s capabilities by utilizing CUDA, TensorRT, and NVIDIA AI Enterprise to optimize AI model development, deployment, and management.