Google Cloud’s MedPerf uses A3 machines with NVIDIA H100 GPUs inside hardware-isolated trusted execution environments for private medical-AI evaluation.

Google Cloud is collaborating with MLCommons on MedPerf, an open-source platform launched in 2023 to standardize medical-AI evaluation. MedPerf uses Google Cloud Confidential Space to create a secure environment for testing proprietary models against real-world patient data.

The workloads run inside hardware-isolated trusted execution environments, or TEEs. These special virtual machines encrypt memory while it is in use and harden the operating system so the hospital, research institution, other participants and Google cannot view the model code or patient data during evaluation.

For GPU-accelerated inference, MedPerf uses Google Cloud A3 machines with NVIDIA H100 GPUs. The configuration combines Intel Trust Domain Extensions on the central processing unit with NVIDIA Confidential Computing on the GPU, extending protection beyond CPU memory to model weights and patient data processed by the accelerator.

Before patient data enters the workload, the system provides cryptographic proof that approved code is running on genuine confidential-computing hardware in a properly hardened environment. The technology is being used by the Federated Tumor Segmentation initiative to validate models against private brain magnetic-resonance-imaging data from multiple locations.