NVIDIA GH200 Grace Hopper Superchip
NVIDIA Grace CPU with Hopper GPU
72-core ARM CPU with H100 96GB GPU. Single module with NVLink-C2C interconnect that delivers 900 GB/s of bidirectional bandwidth between the Grace CPU and Hopper GPU.
Higher Performance and Faster Memory
Higher bandwidth system and GPU memory. 7x faster CPU to GPU transfers over NVLink.
The fastest network for distributed training of LLMs, foundation models & generative AI
Train large foundation models and LLMs with the fastest networking available in any cloud. Our NVIDIA Quantum-2 InfiniBand networking provides 3200 Gbps of bandwidth for each HGX H100, H200, or B200 node.
This design is purpose-built for NVIDIA GPUDirect RDMA with maximum inter-node bandwidth and minimum latency across the entire cluster.
The Lambda compute network uses a non-blocking multi-layer topology with zero oversubscription. This provides full networking bandwidth to every NVIDIA GPU in the cluster simultaneously, the optimal design for full-cluster distributed training.
Skip the CPU and take advantage of GPUDirect RDMA for the fastest distributed training
A direct communication path between NVIDIA GPUs across all nodes in your cluster using NVIDIA Quantum-2 InfiniBand.
GPUDirect RDMA provides a significant decrease in GPU-GPU communication latency and completely offloads the CPU, removing it from all GPU-GPU communications across the network.
Pre-configured for machine learning
Start training your models immediately with pre-configured software, shared storage, and networking for deep learning. All you have to do is choose your NVIDIA GPU nodes and CPU nodes.
Lambda Premium Support for Lambda Private Cloud includes PyTorch, TensorFlow, NVIDIA CUDA, NVIDIA cudNN, Keras and Jupyter. Kubernetes is not included.
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