NVIDIA Magnum IONVIDIA
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NVIDIA RAPIDSNVIDIA
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Related Products
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About
NVIDIA Magnum IO is the architecture for parallel, intelligent data center I/O. It maximizes storage, network, and multi-node, multi-GPU communications for the world’s most important applications, using large language models, recommender systems, imaging, simulation, and scientific research. Magnum IO utilizes storage I/O, network I/O, in-network compute, and I/O management to simplify and speed up data movement, access, and management for multi-GPU, multi-node systems. It supports NVIDIA CUDA-X libraries and makes the best use of a range of NVIDIA GPU and networking hardware topologies to achieve optimal throughput and low latency. In multi-GPU, multi-node systems, slow CPU, single-thread performance is in the critical path of data access from local or remote storage devices. With storage I/O acceleration, the GPU bypasses the CPU and system memory, and accesses remote storage via 8x 200 Gb/s NICs, achieving up to 1.6 TB/s of raw storage bandwidth.
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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
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Mac
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Linux
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Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
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Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
AI researchers, data scientists, and HPC developers needing a tool to eliminate I/O bottlenecks in multi-GPU, multi-node environments
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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
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24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
No information available.
Free Version
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Free Trial
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Reviews/
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Training
Documentation
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Webinars
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Live Online
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In Person
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Training
Documentation
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In Person
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Company InformationNVIDIA
Founded: 1993
United States
www.nvidia.com/en-us/data-center/magnum-io/
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Company InformationNVIDIA
Founded: 1993
United States
developer.nvidia.com/rapids
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Integrations
Apache Spark
Supported
Anaconda
Not Supported
CUDA
Supported
Capital One Spark Business Banking
Not Supported
Databricks
Not Supported
Domino Enterprise AI Platform
Not Supported
Gradient
Not Supported
HEAVY.AI
Not Supported
HPE Ezmeral Data Fabric
Not Supported
IBM Cloud
Not Supported
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Integrations
Apache Spark
Supported
Anaconda
Supported
CUDA
Not Supported
Capital One Spark Business Banking
Supported
Databricks
Supported
Domino Enterprise AI Platform
Supported
Gradient
Supported
HEAVY.AI
Supported
HPE Ezmeral Data Fabric
Supported
IBM Cloud
Supported
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