A parallel file system is a type of file system that is designed to improve performance and scalability by allowing multiple processes to read from and write to a file simultaneously. This is particularly important in high-performance computing (HPC) environments, where large volumes of data need to be processed quickly by many compute nodes. Parallel file systems enhance performance and scalability by enabling simultaneous read and write operations, crucial for high-performance computing environments handling vast data volumes across multiple compute nodes.
Acceleron has two models of Parallel file storage systems:
- APF S100-L: This is a Lustre based HPC storage. Lustre widely used in HPC environments, Lustre is known for its high performance and scalability. It is often used in large-scale supercomputing facilities.
- APF S100-G: This is a GPFS based HPC storage system. GPFS (General Parallel File System) is known as IBM Spectrum Scale, GPFS is a high-performance clustered file system developed by IBM. It is used in various environments, from commercial data centers to research facilities.
Parallel File Systems (PFS) are capable of delivering millions of IOPS which is required for HPC. PFS is essential for environments that require high-speed access to large datasets, enabling efficient data processing and analysis by leveraging multiple servers and storage devices to work in tandem.
Benefits
- High Performance: They allow simultaneous data access by multiple clients, significantly increasing read/write speeds and overall throughput.
- Scalability: Easily scale by adding more storage nodes, accommodating growing data needs without performance degradation.
- Data Distribution: Distribute data across multiple disks or servers, enhancing redundancy and load balancing.
- Fault Tolerance: Provide data redundancy and recovery mechanisms, improving system reliability and minimizing downtime.
- Efficient Resource Utilization: Optimize the use of storage and network resources, reducing bottlenecks and enhancing efficiency in high-performance computing environments.