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feat: acceleration and transport layer #348
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feat: acceleration and transport layer #348
knzo25
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knzo25:feat/cuda_acceleration_and_transport_layer
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Signed-off-by: vividf <[email protected]>
Signed-off-by: vividf <[email protected]>
Signed-off-by: vividf <[email protected]>
Signed-off-by: vividf <[email protected]>
…g and transport layer Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
knzo25
changed the title
feat acceleration and transport layer
feat: acceleration and transport layer
Nov 25, 2024
This was referenced Nov 25, 2024
Note: this PR will be kept as a draft until #337 it merged, at which point this PR will be reabsed |
…cceleration_and_transport_layer Signed-off-by: Kenzo Lobos-Tsunekawa <[email protected]>
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Description
This PR is part of a series of PRs that aim to accelerate the Sensing/Perception pipeline through an appropriate use of CUDA.
List of PRs:
To use these branches, the following additions to the
autoware.repos
are necessary:Depending on your machine and how many nodes are in a container, the following branch may also be required:
https://github.com/knzo25/launch_ros/tree/fix/load_composable_node
There seems to be a but in ROS where if you send too many services at once some will be lost and
ros_launch
can not handle that.Related links
Parent Issue:
How was this PR tested?
The sensing/perception pipeline was tested until centerpoint for TIER IV's taxi using the logging simulator.
Notes for reviewers
The main branch that I used for development is
feat/cuda_acceleration_and_transport_layer
.However, the changes were too big so I split the PRs. That being said, development, if any will still be on that branch (and then cherrypicked to the respective PRs), and the review changes will be cherrypicked into the development branch.
Interface changes
An additional topic is added to perform type negotiation:
Example:
input/pointcloud
->input/pointcloud
andinput/pointcloud/cuda
Effects on system behavior
Enabling this preprocessing in the launchers should provide a much reduced latency and cpu usage (at the cost of a higher GPU usage)