Deliver Business Innovation with GPU-accelerated Machine Learning
H2O4GPU is an open source, GPU-accelerated machine learning package with APIs in Python and R that allows anyone to take advantage of GPUs to build advanced machine learning models. A variety of popular algorithms are available including Gradient Boosting Machines (GBM’s), Generalized Linear Models (GLM’s), and K-Means Clustering. Our benchmarks found that training machine learning models on GPUs was up to 40x faster than CPU based systems.
Key Features of H2O4GPU
- Optimized for GPU Performance
- Broad Selection of GPU Enabled Algorithms
- Builds on scikit-learn Python API
- Available R API
Fully optimized to run on the latest-generation NVIDIA® Volta architecture GPUs, the NVIDIA Tesla® V100 and CUDA 9 software.
Available algorithms include Gradient Boosting Machines (GBM’s), Generalized Linear Models (GLM’s), K-Means Clustering, SVD, PCA, K-means and XGBoost to deliver models and results faster to the business.
H2O4GPU is an open-source collection of GPU solvers created by H2O.ai. It builds on the easy-to-use scikit-learn Python 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.
A new R API brings the benefits of GPU-accelerated machine learning to the R user community. The R package is a wrapper around the H2O4GPU Python package, and the interface follows standard R conventions for modeling.
When AI becomes mission critical for enterprise success, H2O.ai is there to help. H2O Enterprise Support provides the services you need to optimize your investments in people and technology to deliver on your AI vision. H2O Enterprise Support includes training, a dedicated account manager, 24/7 support, accelerated issue resolution and direct enhancement requests. Enterprise support also gives you access to H2O experts in data science, the H2O platform and DevOps/production deployment to accelerate and expand your adoption of AI.Learn More
Featured Use Cases
Providing predictive insights to decision makers and frontline employees is critical to improving customer satisfaction and decreasing operating costs across industries.
Detecting fraud even before it happens can prevent significant losses for financial institutions and prevent headaches for customers that can damage relationships.
Finding ways to improve the claims process can save money but also makes sure that customers and patients with legitimate issues are taken care of.