The “Grace Hopper chip” usually means NVIDIA’s Grace Hopper Superchip, or GH200: a module that combines a Grace CPU with a Hopper GPU, linked by NVIDIA’s NVLink-C2C interconnect. Hopper is the GPU architecture; the H100 is a GPU based on that architecture, not the entire GH200.
What does “Grace Hopper” mean?
NVIDIA uses “Grace Hopper” for a combined CPU-GPU platform. Its name brings together Grace, the CPU, and Hopper, the GPU architecture. NVIDIA named the Hopper architecture in honor of computer scientist Grace Hopper; its March 22, 2022 announcement described Hopper as the successor to Ampere and introduced the H100 as its first Hopper-based GPU. NVIDIA’s announcement
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The term can be confusing because the names overlap: Hopper is an architecture, H100 is a product built on it, and GH200 is the Grace Hopper Superchip that combines a Grace CPU and Hopper GPU.
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The Grace CPU and Hopper GPU are connected by NVLink-C2C, which NVIDIA describes as a memory-coherent chip-to-chip interconnect. NVIDIA states that the connection provides up to 900 GB/s of bandwidth in the Grace Hopper architecture; this is a vendor-stated maximum, not a measured speed guaranteed for every workload. NVIDIA’s Grace Hopper architecture overview
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In NVIDIA’s architecture description, the CPU uses LPDDR5X memory and the GPU uses HBM3 memory. The hardware supports CPU and GPU threads accessing both memory pools without explicit data movement in the programming model. That describes the architecture, not a promise that every application will perform equally well; results depend on the workload and system configuration.
GH200 is a module used in accelerated-computing systems, not a synonym for a complete server or rack. Those systems are larger configurations built around the hardware.
What is it designed for?
NVIDIA positions Grace Hopper for artificial intelligence and high-performance computing, especially workloads that can benefit from large, high-bandwidth memory space and close communication between CPU and GPU. That is the vendor’s intended use, not an independent benchmark finding. A workload’s actual benefit depends on how it uses the CPU, GPU, memory, and interconnect.
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How is Grace Hopper different from H100?
| Name | What it refers to | How it fits |
|---|---|---|
| Hopper | GPU architecture | The architecture used by H100 and the GPU in GH200. |
| H100 | Hopper-based GPU product | A GPU on its own; it is not the Grace Hopper CPU-GPU module. |
| Grace Hopper / GH200 | CPU-GPU Superchip | Combines a Grace CPU and Hopper GPU using NVLink-C2C. |
Specifications also depend on whether a figure describes the full GPU design or a particular H100 product configuration. NVIDIA’s architecture material gives the full GH100 GPU as 80 billion transistors and 814 mm², with 144 streaming multiprocessors (SMs). The same source lists 132 SMs for H100 SXM5 and 114 SMs for H100 PCIe. These are not interchangeable configuration figures. NVIDIA’s Hopper architecture overview
Who was Grace Hopper?
Grace Hopper was a pioneering U.S. computer scientist, and NVIDIA named the Hopper architecture in her honor. NVIDIA’s naming announcement does not say that she designed the modern chip; the name is a tribute.
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