Reduce memory footprint
Open
Nobody has claimed this yet.
enhancement
- Dominant language
- Python
- Stars
- 55
- Forks
- 12
- PR merge metrics
- No merged PRs in 30d
Description
There are a few global operations (scene-wide quantiles, others?) that preclude a simplistic block iteration approach. But we should be able to trade a bit of speed, maybe doing two passes, in order to reduce the memory footprint which is upwards of 5+ GB. We should profile memory usage and think of some ways to reduce it.
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
No files or tests are named. Start by profiling the scene-wide operations and their memory use, then investigate whether two-pass or block-based processing can reduce the footprint; done means demonstrating lower memory usage while preserving results and accepting only the intended speed tradeoff.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- performance
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100