recommenders-team/recommenders

[ASK] Utilizing GPU with LightGCN Pipeline

Open

#1,650 opened on Feb 18, 2022

View on GitHub
 (0 comments) (2 reactions) (0 assignees)Python (2,972 forks)batch import
help wanted

Repository metrics

Stars
 (17,706 stars)
PR merge metrics
 (Avg merge 6d 16h) (10 merged PRs in 30d)

Description

Description

Is there anything that needs to be done to make sure LightGCN is utilizing GPU's? I'm following this deep dive notebook here: https://github.com/microsoft/recommenders/blob/main/examples/02_model_collaborative_filtering/lightgcn_deep_dive.ipynb

My dataset is 1.4M users with about 13M interactions, a single epoch is taking about an hour. I have access to 4 GPU's, 192GB memory.

Thanks!

Contributor guide

Research direction
Check if PyTorch/TensorFlow recognizes GPU by running torch.cuda.is available() or tf.config.list physical devices('GPU'). Ensure the model is moved to GPU with .to(device) or device='/gpu:0'.
Tech stack
python
Domain
backend
Issue type
Documentation
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Under 1 hour
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Python
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75