NVIDIA-Merlin / NVIDIA-Merlin/Merlin
[RMP] Performant large embedding table support
Open
@edknv is already working on this.
Since Feb 28, 2023.
roadmap
- Dominant language
- Python
- Stars
- 907
- Forks
- 129
- PR merge metrics
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Description
Problem:
Goal:
New Functionality
- Models
- ...
- Transformers4Rec
- ...
- NVTabular
- ...
- Systems
- ...
Constraints:
##Architectural consideration
NA
Starting Point:
Model Parallel Support
-
Evaluation of HugeCTR, TorchRec, Distributed Embeddings, TFRA, PersiaML for inclusion in Merlin - Distributed embedding table support in merlin-models (SOK Plugin, Distributed Embeddings)
- Model Parallel Training ( related to SOK integration in Merlin Models )
- Third Gen Embeddings
Feature engineering that reduces embedding size
- Mixed Dimension Embeddings
- Frequency Capping
- Frequency Hashing
- Bloom Embeddings
- TT-Rec
Reduced Precision Support
- Sparse Row-wise Optimizers (Facebook Research DLRM)
- Reduced Precision Optimizers
- Reduced Embedding Precision
Not storing user embeddings
- Represent user as item embedding aggregations (YouTube DNN)
Inference Support
- Hierarchical Parameter Server Support
Serving
Example
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
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