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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.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers, data scientists, and HPC developers needing a tool to eliminate I/O bottlenecks in multi-GPU, multi-node environments

Audience

Enterprises in search of a solution to execute end-to-end data science and analytics pipelines entirely on GPUs

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

NVIDIA
Founded: 1993
United States
www.nvidia.com/en-us/data-center/magnum-io/

Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/rapids

Alternatives

Alternatives

NVIDIA Brev

NVIDIA Brev

NVIDIA

Categories

Categories

Integrations

Apache Spark
Anaconda
CUDA
Capital One Spark Business Banking
Databricks Data Intelligence Platform
Domino Enterprise MLOps Platform
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
IBM Cloud
Iguazio
Intel Tiber AI Studio
Kinetica
NVIDIA FLARE
NVIDIA NetQ
NVIDIA virtual GPU
Nuclio
Plotly Dash

Integrations

Apache Spark
Anaconda
CUDA
Capital One Spark Business Banking
Databricks Data Intelligence Platform
Domino Enterprise MLOps Platform
Gradient
HEAVY.AI
HPE Ezmeral Data Fabric
IBM Cloud
Iguazio
Intel Tiber AI Studio
Kinetica
NVIDIA FLARE
NVIDIA NetQ
NVIDIA virtual GPU
Nuclio
Plotly Dash
Claim NVIDIA Magnum IO and update features and information
Claim NVIDIA Magnum IO and update features and information
Claim NVIDIA RAPIDS and update features and information
Claim NVIDIA RAPIDS and update features and information