Isaac ROS Benchmark

Overview

Isaac ROS Benchmark
-Builds upon the ros2_benchmark to provide configurations to benchmark Isaac ROS graphs
-Performance results that measure Isaac ROS for throughput, latency, and utilization enable robotics developers to make informed decisions when designing real-time robotics applications
Informed Decision-Making:
By benchmarking Isaac ROS graphs, developers can gain insights into the system’s behavior under different conditions and workloads
This information helps them make informed decisions when designing and optimizing real-time robotics applications
For example, it can help identify bottlenecks, resource constraints, or areas for improvement in the system
-The Isaac ROS performance results can be independently verified, as the method, configuration, and data input used for benchmarking are provided
Independent Verification:
Results obtained from the benchmarking process are designed to be independently verifiable
Means that the methods, configurations, and data inputs used for benchmarking are transparent and documented, allowing other developers or users to replicate the benchmarking process and verify the results
-The ros2_benchmark playback node plug-in, for type adaptation and negotiation, is provided for NITROS, which optimizes the performance of message transport costs through RCL with GPU accelerated graphs of nodes
Integration with NITROS:
Package includes a plugin for the “ros2_benchmark” playback node
Plugin is used for type adaptation and negotiation and is designed to optimize the performance of message transport costs through RCL (ROS 2’s middleware) with GPU-accelerated graphs of nodes
This integration aims to improve the efficiency of message communication within Isaac ROS graphs, potentially leveraging GPU acceleration for faster data processing
-Datasets for benchmarking are explicitly not downloaded by default
To pull down the standardized benchmark datasets, refer to the ros2_benchmark Dataset section
Footnote
benchmark: Measure and evaluate the performance of robotic systems built using Isaac ROS
throughput: How much data it can process per unit of time
latency: How quickly it responds to inputs
utilization: How effectively it utilizes system resources

QuickStart

Follow the steps below to run a sample benchmark for measuring performance of an Isaac ROS AprilTag node with ros2_benchmark
This process can also be used to benchmark the other Isaac ROS nodes
-ros2_benchmark framework more generally supports benchmarking arbitrary graphs of ROS 2 nodes
(1)Set up your development environment by following the instructions here
(2)Clone isaac_ros_common and this repository under ${ISAAC_ROS_WS}/src

(3)Pull down r2b Dataset 2023 by following the instructions here or fetch just the rosbag used in this Quickstart with the following command


(4)Launch the Docker container using the run_dev.sh script

(5)Install this package’s dependencies

(6)Start the Isaac ROS AprilTag benchmark

(7)Once the benchmark is finished, the final performance measurements are displayed in the terminal
Additionally, the final results and benchmark metadata (e.g., system information, benchmark configurations) are also exported as a JSON file

Reference:
https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_benchmark/index.html
https://github.com/NVIDIA-ISAAC-ROS/ros2_benchmark#datasets