HPC and AI require high-performance storage
High-performance computing (HPC) and artificial intelligence (AI) workloads are dramatically different than enterprise compute workloads. Instead of small file sizes and enterprise applications, HPC and AI workloads are usually batch jobs with large data sets on large distributed compute clusters. Parallel distributed file systems are typically required to provide high-speed, concurrent access to data.
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Key differences among HPC, AI, and enterprise storage
| | Enterprise storage | HPC storage | AI storage |
|---|---|---|---|
| Typical workload | Transactional | Job (Data Set) | Job (Data set) |
| Performance requirement | IOPS | Bandwidth | Bandwidth |
| Typical file size | Small | Large | Mixed |
| Typical file access | Random | Sequential | Mixed |
| Data movement | Minimal | Extensive | Moderate |
| Read/write intensity | Mixed | Write-intensive | Read-intensive |
Meet the varied storage requirements for HPC and AI
Storage supports compute by providing the data needed for applications and users. HPE provides storage solutions that meet IO requirements, manage data, minimise TCO and streamline data workflows.
WekalO Matrix
HPE Data Management Framework
Scalable Storage for Lustre
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