XGBoost: Scalable GPU Accelerated Learning

Understand

We describe the multi-GPU gradient boosting algorithm implemented in the XGBoost library (https://github.com/dmlc/xgboost).

• Our algorithm allows fast, scalable training on multi-GPU systems with all of the features of the XGBoost library.
• We employ data compression techniques to minimise the usage of scarce GPU memory while still allowing highly efficient implementation.
• Using our algorithm we show that it is possible to process 115 million training instances in under three minutes on a publicly available cloud computing instance.