NVIDIA · March 2022
H100
PCIe
The NVIDIA H100 PCIe is a high-performance GPU designed for data centers, targeting AI, machine learning, and high-performance computing workloads. It is part of the Hopper architecture, offering significant improvements in performance and efficiency over its predecessors. The H100 PCIe variant is optimized for PCIe-based systems, providing flexibility in deployment across a wide range of server configurations.
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Architecture
Memory & VRAM
Connectivity & Scaling
Virtualization
Power & Efficiency
Physical Design
Thermals & Cooling
Software Ecosystem
Server & Deployment
System Compatibility
Benchmarks & Throughput
Scaling Efficiency
Supports NVLink bridging between H100 PCIe cards; document states two-card bridged bandwidth of 900 GB/s bidirectional and lists per-card NVLink maximum bandwidth of 600 Gbytes per second.
Multi-GPU Scalability
Scaling Characteristics
Workload Readiness
HPC / Simulation
true
Market Authority
Key Strengths
The H100 PCIe excels at AI training and inference, offering substantial performance gains in deep learning workloads due to its advanced tensor cores and high memory bandwidth. It is also well-suited for scientific simulations and data analytics, providing a versatile solution for complex computational tasks.
Limitations
While the H100 PCIe offers excellent performance, it lacks NVLink support, which can be a limitation for applications requiring high-speed inter-GPU communication. Additionally, its high power consumption may necessitate upgrades to power delivery systems in some data centers. Availability can be constrained due to high demand and production limitations.
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Expert Insight
The H100 represents a strategic leap in AI compute. When comparing cloud providers, consider not just the hourly rate, but also the interconnect bandwidth (InfiniBand/NVLink) and regional availability which can significantly impact total cost of ownership for large-scale training.