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Addressing Small File Challenges in High-Performance Computing Environments

Small files present significant challenges for file systems in high-performance computing (HPC) environments. Users accustomed to traditional desktop systems often struggle with the transition to HPC without changing their existing workflows. These small files can degrade system performance, especially when managing large data volumes like genomics or natural language processing files. Solutions like parallel file systems, distributed access, and specialized metadata management are essential for improving performance and backup reliability. This presentation addresses potential strategies to overcome small file inefficiencies in HPC setups.

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Addressing Small File Challenges in High-Performance Computing Environments

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Presentation Transcript

  1. Small File File Systems USC Jim Pepin

  2. Level Setting • Small files are ‘normal’ for lots of people • Metadata substitute (lots of image data are done this way) • Comes from ‘pc’/desktop world • These users have discovered ‘hpc’ but don’t want to change programs (not even MPI) • Find ways to help (best is ‘rewrite’ but that is not reasonable to expect) • Small files are deadly to most file systems • Some more than others • Impact of ‘custer’ systems

  3. Level Setting • Disks • Sata • Not fast. • Reliability issues • Cheap • Fast disk (15k etc) • Not cheap • Fast • People are looking at ‘cheap’ • Drives better backup/maintainability solutions • Distributed doesn’t mean ‘faster’ • Virtualization can be your enemy (in some ways)

  4. Basics • 1800 node cluster • Presents special problems • Myrinet ‘interconnect’ • Ethernet (gb) data plane • Fiber channel disk/tape data plane (2Gb/s) • 256+ disk/tape devices • 15+ file servers • 250+ TB disk • Tape Backup • DR site

  5. Basics • QFS base FS • Archiving and distributed access • Sun thing • Local parallel FS on nodes • NFS • Issues around it • “Condo” disk versus Condo nodes

  6. Basics • Three types of File systems • Parallel FS on compute nodes (temp) • Exception on ‘condo’ nodes • Small files • More directory transactions • Small frames win • No stripes • Large files • More data transactions • Jumbo frames win • Stripes win • Tuning is stripe factors and blocksizes

  7. Small Files • Examples • Genomics Group • 10ks of files in single directory • Natural Language Group • 50-250k files in directory • Many nodes accessing same stuff • Dictionaries • Backups are ‘slower’ / ‘harder’ • Reasons • Updating directory data • Blocking of data on tape

  8. Small Files • Ways to help • “Faster” disk (helps metadata/directory space) • Distributed file access (qfs) • Metadata still a ‘block’. • Read/write locks • Updating for distributed access • Next version scales better (lock improvements) • No free lunch • Special Purpose File Systems and/or local space on cluster nodes (replication)

  9. Next generation • Why change needed • NFS doesn’t cut it • Why • GPFS • Helps some • 10Gb hosts on ‘data plane’ • Next month • Ram disk for ‘metadata’?

  10. Next generation • Storage management solutions • SRB and friends • Database based solutions • Lustre possible • Object storage • Performance for small files/objects is question in my mind • All these have potential but… • Back to don’t change code • “Virtualization” conundrum • How to build massively parallel data spaces • HPCS/other projects

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