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What is Sangfor aStor?

Sangfor aStor is a cutting-edge software-defined storage solution that integrates block, file, and object storage into a unified, elastically scalable resource pool, harnessing a fully symmetrical distributed architecture to enable on-demand provisioning of high-performance and cost-efficient storage tiers that meet diverse service requirements. This system can be implemented as an all-in-one hardware-software package or as independent software, scaling from a basic configuration of three commodity x86 nodes to extensive cloud-scale clusters with thousands of nodes, facilitating EB-level capacity expansion. Through its multi-node parallel processing and advanced caching strategies—including RDMA, SSD hot-data caching, and data layering—it delivers remarkable throughput, IOPS, and performance for small I/O operations, significantly boosting cache hit rates up to 90% and enhancing small I/O processing by as much as 65%. Moreover, its distributed metadata management allows for the effective management of billions of files without noticeable latency, solidifying its position as a powerful solution for contemporary storage dilemmas. In conclusion, Sangfor aStor emerges as a dynamic and efficient choice for enterprises aiming to refine their storage architecture while ensuring scalability and performance.

What is NVIDIA Magnum IO?

NVIDIA Magnum IO acts as a sophisticated framework designed for optimizing I/O processes in parallel data center environments. By improving the functionality of storage, networking, and communication across various nodes and GPUs, it supports vital applications such as large language models, recommendation systems, imaging, simulation, and scientific studies. Utilizing storage I/O, network I/O, in-network computation, and well-organized I/O management, Magnum IO effectively accelerates and simplifies the movement, access, and management of data within complex multi-GPU and multi-node settings. Its compatibility with NVIDIA CUDA-X libraries ensures peak performance across a variety of NVIDIA GPU and networking hardware configurations, maximizing throughput while minimizing latency. In architectures that utilize multiple GPUs and nodes, the conventional dependence on slow CPUs with limited single-thread performance poses challenges for efficient data access from both local and remote storage. To address this issue, storage I/O acceleration enables GPUs to bypass the CPU and system memory, facilitating direct access to remote storage via 8x 200 Gb/s NICs, thus achieving an impressive 1.6 TB/s in raw storage bandwidth. This technological advancement substantially boosts the overall operational efficiency of applications that require extensive data processing, ultimately allowing for faster and more responsive data-driven solutions. Such improvements represent a significant leap forward in managing the increasing demands of modern data workloads.

Media

Media

Integrations Supported

Amazon S3
Apache Spark
CUDA
Microsoft Hyper-V
NVIDIA NetQ
NVIDIA virtual GPU
OpenStack
Swift
VMware Cloud

Integrations Supported

Amazon S3
Apache Spark
CUDA
Microsoft Hyper-V
NVIDIA NetQ
NVIDIA virtual GPU
OpenStack
Swift
VMware Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Sangfor

Date Founded

2000

Company Location

China

Company Website

www.sangfor.com/cloud-and-infrastructure/products/astor-enterprise-data-storage-solution

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/data-center/magnum-io/

Categories and Features

Categories and Features

Data Center Management

Audit Trail
Behavior-Based Acceleration
Cross Reference System
Device Auto Discovery
Diagnostic Testing
Import / Export Data
JCL Management
Multi-Platform
Multi-User
Power Management
Sarbanes-Oxley Compliance

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