Parabricks is fully optimized and supported on all systems powered by the NVIDIA Grace CPU architecture — including the NVIDIA GH200 Grace Hopper Superchip, the NVIDIA GB200 Grace Blackwell Superchip, and the NVIDIA GB300 NVL72 system. These platforms combine breakthrough CPU and GPU performance with the world's first truly unified CPU+GPU memory architecture, enabling faster data access, reduced complexity, and accelerated AI and HPC workflows.

All tools in the Parabricks suite leverage the strengths of the Nvidia Grace CPU to maximize performance:

• Vectorized Instructions: Parabricks tools utilize Grace CPU-specific vectorized instructions to accelerate computational tasks.

• NVLink-C2C Interconnect: The high-bandwidth NVLink-C2C link minimizes latency for GPU-CPU data transfers, optimizing hybrid workflows.

• High CPU Core Density: The Arm-based Grace CPU provides up to 72 cores per GPU, reducing CPU bottlenecks in hybrid workloads.

Example Performance: The deepvariant_germline tool processed a 30X Illumina dataset 1.4x faster on an NVIDIA GH200 Grace Hopper Superchip (480GB unified memory) compared to a system with one NVIDIA H100 NVL GPU.

All tools and pipelines from Parabricks 4.6.0-1 are now optimized and supported on the NVIDIA Grace Platforms, therefore we refer the users and developers to the Tool Reference.

To achieve optimal performance for all Parabricks tools on the NVIDIA Grace CPU we refer the users and developers to the Grace CPU benchmarking guide. This guide will illustrate recommendations and best practices directly related to the NVIDIA Grace CPU and help you realize the best possible performance for your particular system.

• Parabricks is available as a multi-architecture container, the same Docker command works across systems - whether using an NVIDIA Grace system or x86 nodes:

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    $ docker pull nvcr.io/nvidia/clara/clara-parabricks:4.6.0-1
          

  and follow the Tutorials.

• For any questions or support, please visit the NVIDIA Parabricks Community. Join a vibrant community of researchers and experts to exchange ideas, seek assistance, and stay updated on the latest developments in genomic data analysis.

• To learn more about the NVIDIA GH200 Grace Hopper Superchip please visit here.

• To learn more about the NVIDIA GB200 Grace Blackwell Superchip please visit here.

• To learn more about the NVIDIA GB300 NVL72 please visit here.