[Documentation] [TitleIndex] [WordIndex

Only released in EOL distros:  

physics_ode: opende | parallel_quickstep

Package Summary

Parallel implementation of quickstep, configurable for CUDA, OpenCL and OpenMP.

The package by default is compiled with CPU quickstep. To enable GPU capabilities, overlay this package and recompile with CUDA drivers installed.

physics_ode: opende | parallel_quickstep

Package Summary

Parallel implementation of quickstep, configurable for CUDA, OpenCL and OpenMP.

The package by default is compiled with CPU quickstep. To enable GPU capabilities, overlay this package and recompile with CUDA drivers installed.

physics_ode: opende | parallel_quickstep

Package Summary

Parallel implementation of quickstep, configurable for CUDA, OpenCL and OpenMP.

The package by default is compiled with CPU quickstep. To enable GPU capabilities, overlay this package and recompile with CUDA drivers installed.

physics_ode: opende | parallel_quickstep

Package Summary

Parallel implementation of quickstep, configurable for CUDA, OpenCL and OpenMP.

The package by default is compiled with CPU quickstep. To enable GPU capabilities, overlay this package and recompile with CUDA drivers installed.

Contents

  1. Overview
  2. Usage

Overview

The parallel_quickstep library is a more or less port of physics_ode/ODE's quickstep method to the GPU, providing implementations in CUDA, OpenCL and OpenMP.

The approach operates by dividing the constraints into batches, where each batch contains as few as possible redundant bodies. At each iteration in the solver, constraints within a batch are operated on in parallel, and batches are operated on serially. Several batching strategies are provided, as well as several reduction strategies for accumulating body accelerations for bodies involved with multiple constraints in a given batch. The typical number of batches is 4 to 5, though that is both configurable and dependent on the size of the simulation.

Usage

The package can be used either as a standalone library with ODE, or directly with Gazebo

The API is similar to that of ODE's quickstep, exposing the method dWorldParallelQuickStep which can be used just as with dWorldQuickStep.

By default, the released version of parallel_quickstep is compiled with CPU support only. To enable dWorldParallelQuickStep with CUDA, please follow these steps:

  1. Install CUDA on your system.
  2. Checkout and install simulator_gazebo from source,

    • Easiest way is to use the rosinstall tool, install it following instructions on the rosinstall wiki.

    • Download simulator rosinstall file in your home directory, and run

      rosinstall ~/diamondback_simulator ~/simulator.rosinstall
    • Rebuild simulator_gazebo stack, if you have previously checked out gazebo or parallel_quickstep locally, make sure to do a make clean first:

      roscd gazebo
      make clean
      roscd parallel_quickstep
      make clean
      rosmake simulator_gazebo

      During recompilation of parallel_quickstep, if CUDA is installed correctly on your system, cmake scripts in parallel_quickstep should detect it automatically. You should see cmake output on the console similar to:

      ...
      -- CUDA Found, compiling with CUDA support
      -- using sm_10 without DOUBLE_SUPPORT_ENABLED and ATOMIC_SUPPORT_ENABLED
      -- CUDA Target Architecture: sm_10
      ...
    • Add the line (or modify as) <stepType>parallel_quick</stepType> to your Gazebo world file

    • Launch the world
  3. Alternatively, you can configure the package for use with either CUDA, OpenCL or OpenMP directly in the base CMakeLists.txt file. Note that this will require the relevant libraries for each implementation, which at this time are not necessarily provided by ROS. For instance, for CUDA you will need NVIDIA's CUDA Toolkit, and for OpenCL you will need a supported driver.


2019-07-13 12:57