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Achieve Optimal Performance for HPC Workloads
Deliver the fastest data access and elasticity, driving innovation and major breakthroughs across HPC industries.
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Cutting-edge Scientific Exploration and Discovery Demand Leading-edge Performance Storage Infrastructure
Process Massive Amounts of Data
HPC workloads like science and engineering simulations, energy exploration, weather prediction and genomics analysis process massive amounts of data accessed by multiple systems simultaneously. Enterprises need data infrastructure that is built to scale and perform for HPC workloads.
Demands for High Performance at Scale
HPC workloads can be notably complex and it has evolved from tools focused on simulation-based scientific investigation to a dual role running simulation and machine learning. A relentless focus on HPC data infrastructure's performance at scale is essential to ensure efficient scientific research and discoveries.
Control Storage Costs
High-performance computing often involves large-scale datasets, which require significant storage resources. By differentiating between hot and cold data based on data lifecycle and storing them on different media respectively, users can reduce the total cost of ownership.
Providing the Highest Efficiency in Processing Massive Data for Your Most Demanding Workflows, Fueling Rapid Innovation and Breakthroughs
YRCloudFile is a high-performance distributed parallel file system optimized for various HPC workloads. It tackles challenges such as throughput and I/O performance bottlenecks associated with large data volumes and overcomes the limitations of traditional file storage systems in terms of elastic scalability, performance, capacity, and the complexities of operations and data management. YRCloudFile delivers rapid data access to HPC facilities, and boosts the productivity of HPC and AI-driven research, accelerating time to results for all users.
Advantages
Exceptional Performance
With support for RDMA/RoCE and NVIDIA Magnum IO GPUDirect™ Storage access, YRCloudFile delivers ultra-high performance, enabling research teams to gain results and insights more quickly.
Unified Namespace
Simplify data management and provide real-time access to data—whether on-premises, at the edge, or in the cloud—with YRCloudFile's unified namespace.
Flexible Data Growth
Storage capacity scales horizontally to satisfy the demands of rapidly growing data volume, whethter PB or EB-scale.
Persistent Container Storage
A multi-cloud-ready container storage platform that meets the demand of containerization for high performance computing systems.
Multiple Access Protocols
Supports multiple data access protocols including POSIX, CSI, HDFS, NFS, SMB, etc. for massive unstructured data.
Archive Economics
Intelligent tiering feature automatically offloads cold data to object storage, effectively reducing total cost.