RAPIDS
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About
RAPIDS is a suite of open-source software libraries that provides GPU acceleration for data science and analytics pipelines. It integrates with popular PyData libraries like Pandas and scikit-learn, allowing users to speed up their existing workflows with minimal code changes. RAPIDS is built on Apache Arrow and NVIDIA CUDA, leveraging the power of GPUs to provide significant performance improvements. It offers components such as cuDF for DataFrame manipulation, cuML for machine learning algorithms, and cuGraph for graph analytics. The tool provides flexibility in deployment, offering installation options via Conda, pip, and Docker. Additionally, RAPIDS can be accessed via cloud-based hardware from various providers such as Google CoLab and Microsoft Azure.
Platform
Features
• open source ecosystem
• gpu accelerated data science
• cloud-based hardware access through google colab, studio lab, paperspace, nvidia launchpad, microsoft azure, oracle cloud, and ibm cloud
• options for installation with conda, pip, and docker
• integration with dask, networkx, nuclio, numba, scikit-learn, and xgboost
• support for cudf, cuml, and cugraph
• integration with apache arrow and nvidia cuda
• accelerates pandas, scikit-learn, and networkx workflows with zero code change
Pricing Plans
Open Source
Free Plan• GPU-accelerated data science libraries
• Integration with cloud platforms
• Open-source access
Job Opportunities
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