This is the PyTorch implementation for the paper entitled "A Two-Stream Light Graph Convolution Network-based Latent Factor Model for Accurate Cloud Service QoS Estimation", which has been acceppted by ICDM2022.
We implement all the experiments in Python 3.7, except that the compressed sparse matrix parallel program is written with CUDA C and compiled with CUDA 11.1. All empirical tests are uniformly deployed on a server with a 2.4-GHz Intel Xeon 4214R CPU, four NVIDIA RTX 3090 GPUs, and 128-GB RAM.
pip install -r requirements.txt
Two real QoS data collected by the WS-Dream system are applied in our experiments, which are the largest publicly-available QoS datasets and widely adopted in prior studies.
Please tune the hyper parameters in run.py
and run it.