-
Notifications
You must be signed in to change notification settings - Fork 20
Home

Actual Application Usage
SPEC Viewperf12
It is not meant to be an exhaustive tool but rather a small and simple to use tool that does not require manual configuration and collects just enough information to present a meaningful overview of how the resources are consumed to better allocate sufficient resources before attempting to shift to a virtual environment.
The tool is named GPUProfiler because it captures a resource "profile" of the application from a GPU perspective over a duration where a user would perform their daily work to characterize what system resources are currently in most demand. This tool is not a "profiler" from a programmer's tool perspective.
S6504 - A Data-Driven Methodology for NVIDIA GRID™ vGPU™ Sizing
[S7396 - Zen and the Art of vGPU Selection ] (https://gputechconf2017.smarteventscloud.com/connect/sessionDetail.ww?SESSION_ID=110301)
- Captures basic system information (CPU, memory, BIOS, OS, GPU, frame-buffer size, VBIOS, driver version)
- Collects the following metrics over a user defined period of time and sampling interval
- CPU utilization
- System memory utilization
- GPU utilization (in non-vGPU environments)
- GPU frame-buffer utilization
- Exports metrics to CSV for further analysis
- Saves system and profile data in a GPD file format for later viewing or analysis.
Currently, GPUProfiler is a VM-level utilization profiling tool. If you wish to collect utilization metrics for a hypervisor host and the host is utilizing an NVIDIA capabile GRID or Tesla card in conjunction with the NVIDIA vGPU Manager, then you may use the nvidia-smi command to collect GPU specific metrics.
Here is an example query that I have used to collect utilization data in CSV format.