How to Query GPU Memory Usage by PID Using nvidia-smi скачать в хорошем качестве

How to Query GPU Memory Usage by PID Using nvidia-smi

Learn how to efficiently query GPU memory usage for specific processes using their PIDs with nvidia-smi, a powerful command-line tool for NVIDIA GPUs. --- This video is based on the question https://stackoverflow.com/q/75282085/ asked by the user 'JoJolyne' ( https://stackoverflow.com/u/12324384/ ) and on the answer https://stackoverflow.com/a/75285620/ provided by the user 'paleonix' ( https://stackoverflow.com/u/10107454/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Query GPU memory usage and/or user by PID Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Efficiently Querying GPU Memory Usage by PID with nvidia-smi Managing GPU resources is critical, especially when running multiple processes and applications. If you ever wondered how to query GPU memory usage for specific processes using their Process IDs (PIDs), you might have found the command-line outputs from NVIDIA's nvidia-smi tool quite complex. But don't worry—this guide is here to guide you through an easy solution! The Problem: Obtaining GPU Memory Usage by PID Imagine you have several processes running across different GPUs, and you need to monitor the GPU memory used by each of them. The default output from nvidia-smi may look sophisticated and is geared more towards human readability than automation, making it tricky to extract the exact information you seek. The key challenge is filtering out the necessary details, such as the used memory per PID. The Solution: Using nvidia-smi Effectively Luckily, nvidia-smi is versatile and offers options for straightforward querying. Here’s how to get the GPU memory usage by PID step by step: Step 1: Use the Right Command Options To retrieve the GPU memory used by processes based on their PIDs, we can make use of the following nvidia-smi command options: --query-compute-apps=pid,used_memory: This option specifies that we want to query the PID and the amount of used_memory for compute applications running on the GPU. --format=csv,noheader,nounits: This formats the output into a simple CSV format without headers and units, making it easier for scripting or further processing. Step 2: Execute the Command Put it all together in the command line like this: [[See Video to Reveal this Text or Code Snippet]] Executing this command will yield results that look something like this: [[See Video to Reveal this Text or Code Snippet]] This output indicates which PID is using how much GPU memory in a clean, machine-readable format. Step 3: Additional Resources To dive deeper into the capabilities of nvidia-smi, consider checking the man pages by running: [[See Video to Reveal this Text or Code Snippet]] This will provide you with comprehensive documentation on all available options and features. Conclusion Querying GPU memory usage by PID using nvidia-smi is not only feasible but can be done efficiently with the right command line options. By leveraging the specified flags, you can streamline your workflow and monitor GPU usage effectively. Whether you are a researcher or a data scientist, having this skill can prove vital for optimizing resource allocation in your GPU workloads. Next time you want to assess the GPU memory footprint of your processes, remember to use this simple command, and you'll have your answer in seconds!