NVIDIA-Merlin / NVIDIA-Merlin/Transformers4Rec
Benchmark the new PyT data loader (with sparse tensors support) scalability with multi-GPU and larger datasets
Open
@rnyak is already working on this.
Since Jun 8, 2021.
Multi-GPU
- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 165
- Avg merge
- 1m
- Merged PRs (30d)
- 2
Description
Benchmark the new PyT data loader with the REES46 ecommerce dataset, using multiple GPUs
Train set: All train.parquet files for 31 days (1 parquet file by week). P.s. Set row group size accordingly
Eval set: All valid.parquet files concatenated
- Create a recsys_main.py variation for non-incremental training
- Train with 3 weeks and evaluate on the last week
- Run experiments varying the number of GPUs: Single GPU, Multi-GPU Data Parallel, Multi-GPU Distributed DataParallel
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.
Assessment
This issue has not been assessed yet.