GPU Compute and memory benchmarks for Jetson AGX Orin

[virtual.ramblings]

We are looking for benchmarks that can give the peak FLOP/s and memory bandwidth on the Jetson AGX Orin.

https://github.com/NVIDIA-AI-IOT/jetson_benchmarks: We looked at this, and it seems to focus on deep learning workloads. We are interested in measuring the peak performance/bandwidth. Please recommend any standard benchmarks.

[carolyuu]

Hi,
Here are some suggestions for the common issues:

1. Performance

Please run the below command before benchmarking deep learning use case:

$ sudo nvpmodel -m 0
$ sudo jetson_clocks

2. Installation

Installation guide of deep learning frameworks on Jetson:

• TensorFlow: Installing TensorFlow for Jetson Platform - NVIDIA Docs
• PyTorch: Installing PyTorch for Jetson Platform - NVIDIA Docs
  We also have containers that have frameworks preinstalled:
  Data Science, Machine Learning, AI, HPC Containers | NVIDIA NGC

3. Tutorial

Startup deep learning tutorial:

• Jetson-inference: Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson
• TensorRT sample: Jetson/L4T/TRT Customized Example - eLinux.org

4. Report issue

If these suggestions don’t help and you want to report an issue to us, please attach the model, command/step, and the customized app (if any) with us to reproduce locally.

Thanks!

[DaneLLL]

Hi,
You may try this stress test:

Jetson/L4T/TRT Customized Example - eLinux.org

[virtual.ramblings]

Is there a similar recommended benchmark to measure memory bandwidth that the GPU is able to effectively get?