GPU-Enabled Data Science & Machine Learning
If you're interested in the NVIDIA academic grant program you can learn more here.
Use NVIDIA GPUs to speed up your data science by up to 2000x on Saturn Cloud
Dask on GPUs
Dask integrates with RAPIDS cuDF, XGBoost, and RAPIDS cuML for GPU-accelerated data analytics and machine learning.
Speed up Python with minimal code changes by using the GPU powered versions of many popular Python libraries like PyTorch.
The right size resource
Choose from a selection of instance sizes with different numbers of GPUs, or connect them together.
Accelerate Model Runtime by 2000x with RAPIDS
Out-of-the-box support and easy setup
Greater Model Accuracy
Increase machine learning model accuracy by iterating on models faster
Reducing Training Time
Improve your productivity with the fastest data science capabilities on market
Customizable, extensible, interoperable – the open-source software is supported by NVIDIA and built on Apache Arrow.
Random Forest on GPUs: 2000x Faster than Apache Spark
We trained a random forest model using 300 million instances: Spark took 37 minutes on a 20-node CPU cluster, whereas RAPIDS took 1 second on a 20-node GPU cluster. That’s over 2000x faster with GPUs.Read more
Accelerate common data science workloads on GPUs with RAPIDS
Dive into example notebooks using a GPU with RAPIDS, scaling to a cluster with Dask, then some runtime comparisons.Read more