H2O4GPU is an open-source collection of GPU solvers created by H2O.ai. It builds on the easy-to-use scikit-learn API and its well-tested CPU-based algorithms. It can be used as a drop-in replacement for scikit-learn with support for GPUs on selected (and ever-growing) algorithms. H2O4GPU inherits all the existing scikit-learn algorithms and falls back to CPU algorithms when the GPU algorithm does not support an important existing scikit-learn class option.
Today, select algorithms are GPU-enabed. These include Gradient Boosting Machines (GBM’s), Generalized Linear Models (GLM’s), and K-Means Clustering.
Gradient Linear Model (GLM)
- Framework utilizes Proximal Graph Solver (POGS)
- Solvers include Lasso, Ridge Regression, Logistic Regression, and Elastic Net Regularization