Scalable Python Analytics with GPUs:
Within seconds of signing up, spin up a JupyterLab instance with pre-configured environments for the most popular GPU data science packages, backed by an NVIDIA T4 or V100 GPU. If your data exceeds a single GPU, you can easily scale out to a cluster of hundreds of GPU machines.
Saturn Hosted takes care of all the hardware provisioning, environment setup, and cluster communication challenges so data scientists can get straight to work.
The Power of Dask
Dataframes for big data
Dask DataFrames are just like Pandas DataFrames, except the data and computation are sharded on a cluster of machines.
Executing Functions on a Cluster
Dask Delayed is a decorator you can apply to any function. Delayed functions can be chaiend together, and executed in parallel on a cluster. As long as you can write functions, we can parallelize your code.
Scale Up to GPUs
GPUs are much faster than CPUs but traditionally they have been very hard to program. With RAPIDS and Numba, leveraging GPUs is easy. Combine that with Dask, and you can execute on multiple GPUs in parallel.
GPU Data Science For Everyone
GPU computing is the future of data science. Packages such as RAPIDS, TensorFlow, and PyTorch enable lightning-fast processing for all facets of data science: data cleaning, feature engineering, machine learning, deep learning, and more. Anyone can access this with Saturn Cloud Hosted: A cloud-hosted solution for end-to-end GPU data science that fits the needs of all startups, small teams, students, researchers, and tinkering data scientists.