Perlmutter GPU partition

NERSC provides Perlmutter for open scientific computing, including GPU-accelerated simulation and AI.

Perlmutter GPU partition is an operational GPU cluster run by NERSC in Berkeley, California, United States. It has 7,168 NVIDIA A100 40GB and 80GB GPUs installed.

Supercomputer

Verified 11 Nov 2026

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Facts

Source per value

Owner / operator Organization that owns or operates the GPUs. Hosting and facility roles are listed under Partners.: NERSC 1
GPU maker NVIDIA, AMD or Intel, taken from the GPU model.: NVIDIA 1
GPU model Accelerator model or family as disclosed. A GH200 is one GPU on a superchip; an MI300A is an APU that contains a GPU.: NVIDIA A100 40GB and 80GB 1
GPUs installed Physical GPUs in the cluster, from the operator or a deterministic sum of disclosed quantities (nodes × GPUs per node). Planned counts, H100-equivalents and unaudited press totals are never counted here.: 7,168 1
GPU count notes What the count covers (one partition, one site, a design limit), qualifiers and competing figures.: Derived compute-partition count: (1,536 + 256) nodes × 4 GPUs; login GPUs excluded. 1
Location City, region and country where the cluster sits. Empty when the operator does not name the site.: Berkeley, California, United States 1
Country Country of the cluster, taken from the location.: United States 1
Live power MW Power in service, in megawatts of IT load where the source says so. Company figures are marked in the notes; Epoch AI satellite estimates are labelled as estimates.: Not published
Status operational = running and named as such by the operator or a primary source; partly operational = a phase is live and more is coming; under construction = building underway; announced = disclosed or contracted with no confirmed go-live.: operational 1
Status notes The source’s wording on status, with the date.: Listed in the operator’s current user documentation. 1
Interconnect Cluster network fabric.: HPE Slingshot 11 1
Compute nodes nodes Compute nodes in the system or partition.: 1,792 1

Sources

docs.nersc.gov accessed 2026-11-11

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