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AI deep learning high-performance storage

YRCloudFile builds a set of distributed file storage with infinite horizontal expansion of capacity and performance for AI users through standard X86 devices, and provides concurrent access support for tens of thousands of clients of deep learning pl...

Data is what drives the AI revolution

YRCloudFile uses the standard X86 server on the market to build a set of distributed file storage with unlimited capacity and performance, which can carry tens of billions of small files of tens of KB, and provide concurrent access support for tens o...

High-performance data access shortens the training process

High-performance storage shorters IO access paths

Support for networks based on the RDMA (Remote Direct Memory Access) protocol, such as IB networks, improves the efficiency of concurrent data processing

By improving the performance of the file system, the GPU is continuously in a state of high efficiency, thus shortening the deep learning training time

Hosting massive files will no longer be a problem

The deep learning training process is based on massive files, and the scale of data is the key means for artificial intelligence enterprises to improve the accuracy of models. Various artificial intelligence enterprises iterate billions of pictures a...

The YRCloudFile metadata cluster can be expanded online on demand, and a single cluster can carry tens of billions of files. The file access performance does not degrade in massive file scenarios, and the number of files carried by a single file syst...

Multi-level intelligent cache reduces data loading across the network

In the model training stage of AI deep learning, the data volume of each training set is about several hundred GB to several TB, and the IO is mainly read. The traditional distributed file system can only improve the data loading performance of the c...

YRCloudFile intelligent cache technology, fully transparent to AI training tasks, combined with AI-oriented replacement algorithm, greatly improve the hit rate of data loading during the training process, data loading performance can be increased by ...

Provide data for containerized training tasks

AI enterprises are increasingly using the Kubernetes orchestration platform to schedule training tasks and resources such as Gpus, and training tasks are gradually running in containers.

From the product positioning, YRCloudFile has designed a large number of container-oriented Persistent storage functions, including Quota configuration at the Persistent Volume level, QoS speed limit, ACL control and so on.

These capabilities enable Kubernetes to plan and schedule YRCloudFile storage capabilities, and enable training tasks to manage and access training data in YRCloudFile via PV.

YRCloudFile Architecture of high-performance distributed file storage

Product

YRCloudFile High-performance distributed file storage

YRCloudFile is a high-performance distributed file storage system launched by Yrong Technology, which provides high-performance, high-availability and high-scalability file access interfaces, supports mainstream container orcheentation frameworks suc... MORE

Product Consultation

F8000X series flash storage machine

Full flash distributed storage machine Yanrong F8000X series is a new generation of full flash distributed file storage machine products created by Yanrong Technology in order to perfectly match the data processing needs of GPU. It is equipped with t... MORE

Product Consultation