NVIDIA 4‑way NVLink Bridge for H200 NVL

The NVIDIA 4-Way NVLink Bridge for H200 NVL is a high-speed interconnect solution that enables seamless communication between four NVIDIA H200 NVL GPUs. Designed specifically for data centers and AI supercomputing platforms, this bridge harnesses the power of NVIDIA’s NVLink technology to deliver exceptional GPU-to-GPU bandwidth, reduced latency, and a unified memory pool.

It plays a critical role in maximizing performance across AI training, deep learning, LLM (Large Language Model) development, and HPC workloads where fast, direct inter-GPU data exchange is essential.

Key Features:

1. Ultra-Fast Inter-GPU Communication

• • Enables direct peer-to-peer access between H200 NVL GPUs for maximum compute efficiency.

2. Scalability for AI & HPC Workloads
   • Supports multi-GPU configurations in AI training, inference, and large-scale simulations.

3. Unified GPU Memory Pool
   • Allows multiple GPUs to access and share memory, critical for memory-intensive tasks like LLMs and deep neural networks.

4. Optimized for NVLink Architecture
   • Utilizes NVIDIA’s high-speed NVLink protocol to surpass traditional PCIe performance limits.

Applications:

1. AI Training & Inference

1. • Accelerate the training of deep learning models, including LLMs and generative AI systems (e.g., GPT, BERT, DALL·E).

2. High-Performance Computing (HPC)

1. • Suitable for large-scale simulations in physics, climate modeling, genomics, and fluid dynamics.

3. Large Language Model (LLM) Development

1. • Provides the high-throughput communication necessary to scale transformer-based models across GPUs.

Why Choose NVIDIA T400 Enterprise 4GB?

1. Unlock Full GPU Potential

1. • Eliminates PCIe bottlenecks and ensures your multi-GPU systems operate at full capacity.

2. Future-Proof AI Infrastructure

1. • Built for next-gen AI platforms requiring massive compute scalability and memory bandwidth.

3. Reduced Overhead, Maximum Efficiency

1. • Lower latency and reduced CPU-GPU data transfer dependencies mean faster model training and better system utilization.