Simulation / Modeling / Design

SC20 Demo: Accelerate HPC Application Performance with NVTAGS

AI-Generated Summary

  • NVIDIA Topology Aware GPU Selection (NVTAGS) automatically profiles HPC application communication and maps MPI processes to GPUs to reduce congestion on GPU-to-GPU links.
  • The toolset extracts system GPU communication topology using NVIDIA System Management Interface (nvidia-smi) and finds an efficient process-to-GPU assignment that minimizes communication delays.
  • NVTAGS is lightweight, with profiling overhead under 1% of total application runtime, and is portable for deployment on systems or within containers.

Next Steps

  • Learn more about NVTAGS to understand how it optimizes GPU communication.
  • Download and deploy NVTAGS to improve HPC application performance.
  • View all SC20 Demos for additional HPC acceleration examples.
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Many GPU-accelerated HPC applications spend a substantial portion of their time in non-uniform, GPU-to-GPU communications, resulting in an increased solution times. 

To ensure that GPU-to-GPU communication is as efficient as possible for HPC applications with non-uniform communication, it is crucial that these applications make informed decisions when assigning MPI processes to GPUs, ensuring processes requiring heavy communication use faster communication links. 

NVIDIA Topology Aware GPU Selection (NVTAGS) is a toolset for HPC applications using MPI. It enables faster solve times for those applications with high GPU-communication-to-application runtime ratios by automatically profiling the application communication, extracting the system GPU communication topology leveraging NVIDIA System Management Interface (nvdia-smi), and finding an efficient process-to-GPU assignment that minimizes communication congestion.

Key benefits of NVTAGS:

  • Automated process: NVTAGS provides a fully automated process that removes the need to conduct manual and time-consuming mapping of GPUs to processes. 
  • Improved performance: NVTAGS dramatically improves performance by intelligently mapping MPI processes to GPUs for HPC applications that require heavy GPU-to-GPU communication. 
  • Lightweight: It is extremely lightweight, with application profiling taking up less than 1% of the total application runtime. It is also very portable and can be easily deployed on a system or integrated within a container. 

Learn More About NVTAGS>
Download and Deploy NVTAGS>
View all SC20 Demos> 

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