Real-time deep learning inference Ai solves a wide array of business challenges, using an equally wide array of neural networks. A great ai inference accelerator has to not only deliver the highest performance but also the versatility to accelerate these networks. H100 extends nvidia??s market-leading inference leadership with several advancements that accelerate inference by up to 30x and deliver the lowest latency. Fourth-generation tensor cores speed up all precisions, including fp64, tf32, fp32, fp16, int8, and now fp8, to reduce memory usage and increase performance while still maintaining accuracy for llms. Transformational AI Training H100 features fourth-generation Tensor Cores and a Transformer Engine with FP8 precision that provides up to 4X faster training over the prior generation for GPT-3 (175B) models. The combination of fourth-generation NVLink, which offers 900 gigabytes per second (GB/s) of GPU-to-GPU interconnect; NDR Quantum-2 InfiniBand networking, which accelerates communication by every GPU across nodes; PCIe Gen5; and NVIDIA Magnum IO software delivers efficient scalability from small enterprise systems to massive, unified GPU clusters. Deploying H100 GPUs at data center scale delivers outstanding performance and brings the next generation of exascale high-performance computing (HPC) and trillion-parameter AI within the reach of all researchers. Experience nvidia ai and nvidia H100 on nvidia launchpad Securely Accelerate Workloads From Enterprise to Exascale NVIDIA H100 is a high-performance GPU designed for data center and cloud-based applications, optimized for AI workloads designed for data center and cloud-based applications Based on the NVIDIA Ampere architecture, it has 640 Tensor Cores and 160 SMs, delivering 2.5x more compute power than the V100 GPU With a memory bandwidth of 1.6TB/s and PCIe Gen4 interface, it can handle large-scale data processing tasks efficiently Advanced features include Multi-Instance GPU (MIG) technology, enhanced NVLink, and enterprise-grade reliability tools
