NVIDIA H100 PCIE High performance graphics processor

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NVIDIA H100 PCIE

The NVIDIA H100 PCIe module is a high-performance graphics processor (GPU) acceleration card from Nvidia Corporation designed for data center and high-performance computing (HPC) environments. It is based on NVIDIA’s Hopper architecture and is designed to accelerate applications in areas such as artificial intelligence, machine learning, and high-performance computing. The H100 has achieved significant improvements in performance and energy efficiency, and is widely used in a variety of scenarios requiring high-performance computing.

Product characteristics

Excellent performance: The H100 delivers powerful computing power that significantly accelerates deep learning, natural language processing, scientific computing and more.
Large-capacity memory: Equipped with large-capacity high-bandwidth memory, can handle massive data, improve training and reasoning efficiency.
High-bandwidth port: Connects to the server through PCIe 5.0 x16 ports, providing high-speed data transmission capability.
Multi-precision calculation: Support a variety of data accuracy, including FP64, FP32, FP16, INT8, etc., to meet the needs of different applications.
Energy efficient: Advanced processes and architectures provide powerful performance while achieving high energy efficiency.
New Transformer engine: delivers up to 9x AI training and up to 30x AI reasoning acceleration on large language models.
Grace CPU Superchip: Some models work with the Grace CPU to achieve tight coupling of the CPU and GPU to further improve performance.
Product parameters (typical values, specific parameters are subject to official data)
GPU architecture: Hopper
Number of CUDA cores: [Specific value varies according to the model]
Memory capacity: 80GB HBM3e
Memory bandwidth: [Specific value, depending on the model]
Port: PCIe 5.0 x16
Power consumption: [Specific value, depending on the model]
Supported apis: CUDA, cuDNN, TensorRT
Product application
Artificial intelligence training: large-scale language model training, computer vision model training
High performance Computing: scientific computing, engineering simulation, financial analysis
Data analysis: Big data processing, data mining
Cloud computing: cloud-based AI-accelerated services