NVIDIA RAPIDSNVIDIA
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Related Products
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About
JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential.
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About
The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. Accelerate your Python data science toolchain with minimal code changes and no new tools to learn. Increase machine learning model accuracy by iterating on models faster and deploying them more frequently.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python
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Audience
Enterprises in search of a solution to execute end-to-end data science and analytics pipelines entirely on GPUs
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationJAX
United States
docs.jax.dev/en/latest/
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Company InformationNVIDIA
Founded: 1993
United States
developer.nvidia.com/rapids
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Categories |
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Integrations
AWS EC2 Trn3 Instances
Anaconda
Capital One Spark Business Banking
Domino Enterprise AI Platform
Equinox
Flower
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
Hugging Face
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Integrations
AWS EC2 Trn3 Instances
Anaconda
Capital One Spark Business Banking
Domino Enterprise AI Platform
Equinox
Flower
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
Hugging Face
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