HPC Visualization Containers

NGC HPC Visualization DGX Software Stack

VISUALIZE YOUR SCIENCE

Visualization is an integral part of scientific computing and data analysis workflows. Interactively viewing the entire dataset in high fidelity accelerates the discovery process. However, installing visualization tools on a multi-tenant system is challenging.

NVIDIA GPU Cloud (NGC) offers high performance computing (HPC) visualization containers that eliminate the need for cumbersome installations. The containers include ParaView, NVIDIA IndeX volume renderer, NVIDIA OptiX ray tracing tool, NVIDIA Holodeck, and NVEnc for remote visualization. Simply pull the latest visualization containers from NGC, and run it on NVIDIA Pascalâ„¢ and NVIDIA Volta-powered systems for interactive real-time visualization and high-quality visuals.

THREE REASONS WHY

  1. Delivering Real-time Visualization in ParaView

    Surface rendering is a time consuming and an iterative process while volume rendering is extremely slow on a CPU system. The HPC visualization containers are optimized to run ParaView on NVIDIA GPUs so that users can seamlessly take advantage of NVIDIA IndeX volume visualization and NVIDIA Optix ray tracing libraries to render scientific data in real-time. NVIDIA HPC visualization containers bundle these technologies with ParaView so that the user can simply pull and run the containers for enhanced ParaView performance on GPUs.
  2. Deploying Visualization Tools

    Containers eliminate the need to install applications on a system, giving users more freedom to run their visualization jobs on different systems. Users can now pull the HPC visualization containers from NGC and run ParaView, NVIDIA IndeX, NVIDIA Optix, and NVIDIA Holodeck on Pascal and Volta GPU-powered workstations, HPC clusters, NVIDIA DGX Systems, and in the cloud. This means that the users no longer have to rely on the system administrators to install the visualization tools.
  3. Driving Low Latency Remote Visualization

    Remote visualization allows users to simulate and visualize their data on a remote system while the rendered frames are sent back for visual analysis. However, the data between frames is 90% identical, which creates a network bottleneck. NVEnc only sends unidentical data between frames which reduces network traffic, lowers latency, and provides faster results.

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