NVIDIA-Merlin / NVIDIA-Merlin/Merlin
[FEA] Calculate minimum required GPU memory for dataloader
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- Dominant language
- Python
- Stars
- 907
- Forks
- 129
- PR merge metrics
- No merged PRs in 30d
Description
🚀 Feature request
Merlin dataloader loads training data in chunks into GPU memory. TensorFlow and Merlin dataloaders need to share the GPU memory. As a user, I want to calculate the minimum required GPU memory for the dataloader, that I know how to configure TensorFlow (providing it the maximum possible GPU memory). Currently, I run a lot of try and error to configure TensorFlow and run into OOM between TensorFlow and the data loader
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 by locating the Merlin dataloader's chunk-loading and GPU-memory configuration, then inspect how it shares memory with TensorFlow. The issue does not name files or tests; clarify the calculation inputs, supported configurations, and validation needed before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100