NVIDIA / NVIDIA/Deep-Learning-Accelerator-SW
How to view DLA utilization rate ?
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Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 236
- Forks
- 24
- PR merge metrics
- No merged PRs in 30d
Description
My process is running, tegrastats or nsys not works.
cat /sys/devices/platform/host1x/15880000.nvdla0/power/runtime_status #DLA0
cat /sys/devices/platform/host1x/158c0000.nvdla1/power/runtime_status #DLA1
https://docs.nvidia.com/nsight-systems/UserGuide/index.html
https://github.com/lix19937/history/tree/main/orin/nsight
LayerwiseStats
https://github.com/NVIDIA/Deep-Learning-Accelerator-SW/tree/main/samples/cuDLA/cuDLALayerwiseStatsStandalone
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the runtime_status commands in the issue, then review the linked Nsight Systems guidance, history/orin/nsight, and cuDLALayerwiseStatsStandalone sample. Determine whether these references provide a supported utilization measurement, and document the applicable procedure and expected output.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- linux, shell
- Domain
- embedded-iot, observability
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100