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Semantically-Smart Disk Systems

Semantically-Smart Disk Systems. Muthian Sivathanu, Vijayan Prabhakaran, Florentina Popovici, Tim Denehy, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau University of Wisconsin, Madison. The Storage Protocol Stack. A Tale of Two Layers. Two layers: The file system and RAID

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Semantically-Smart Disk Systems

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  1. Semantically-Smart Disk Systems Muthian Sivathanu, Vijayan Prabhakaran, Florentina Popovici, Tim Denehy, Andrea Arpaci-Dusseau, Remzi Arpaci-Dusseau University of Wisconsin, Madison

  2. The Storage Protocol Stack

  3. A Tale of Two Layers • Two layers: The file system and RAID • Origins: The hardware/software boundary • S/W: The file system • H/W: The disk • Each increasingly complex • Each a world unto itself • Separated by a narrow interface (SCSI) File System RAID

  4. Your Innovations In Storage:Where In The Stack Should They Go?

  5. Option #1: In The File System • Put innovations in the file system! • Pros: • Lots of semantic information(directories, files, inodes) • Well-defined interfaces (vnode/VFS) • Cons: • No low-level information(head position, RAID scheme) • Hard to deploy: Many FS’s out there • File systems change slowly • FFS [1984] -> ext2 [2002] File System RAID

  6. Option #2: In The RAID • Put innovations in the RAID system! • Pros: • Lots of low-level knowledge • Easy to deploy, sell • Lots of “smarts” (CPUs + Memory) • Cons: • “A stream of block reads + writes,full of bits & bytes, signifying nothing”(no semantic knowledge) File System RAID

  7. The Root Of The Problem: Narrow Interfaces • Narrow interfaces stifle info flow • SCSI to file system: Linear array of blocks • SCSI to disk system:Stream of block reads and writes • Result: Innovation is limited • No “FS-like” innovations in RAID • Anything where info from BOTHsubsystems is required can’t be done File System SCSI RAID

  8. So What’s A Storage-SystemInnovator To Do?

  9. The Ideal Solution? • Exploit raw processing and memory of RAID • Built in low-level knowledge • Easy to deploy • Keep interface the same • Assume traditional file system/RAID boundary • Acquire semantic information of file system • Learn about files, directories, inodes, andother file system data structures

  10. Semantically-Smart Disk System (SDS) • Disk system that understands file system • Data structures • Operations • Operates underneath unmodified FS • Must discover layout + on-disk structures • Must “reverse engineer” block stream • Exploits knowledge and “smarts” to implement new class of services File System SDS CPU $

  11. Outline • Motivation • Semantic Knowledge: Acquisition • Semantic Knowledge: Exploitation • Case studies • Conclusions

  12. Data I-Bitmap D-Bitmap Inodes Data I-Bitmap D-Bitmap Superblk Inodes Static Knowledge: File System Layout • Challenge: How to discover layout information? • White-box approach: Embed knowledge in SDS • Trend: FS layout does not change frequently Group 1 Group 2

  13. Have Knowledge, Will Innovate • Knowing structures is not enough (sometimes) • Data block overloading (data, pointer, directory) • High-level operations not known (create, delete) • Requires new on-line techniques • Direct classification • Indirect classification • Block association • Operation inferencing

  14. I-Bit I-Bit Data D-Bit D-Bit Inode Super Data Inode Direct Classification • Given address, determine type directly • Direct classification via bounds check • Given disk address, can check bounds to determine type(superblock, bitmaps, inodes, general data block)

  15. I-Bit Data I-Bit D-Bit D-Bit Inode Super Data Inode Beyond Simple Meta-Data • Want to cache other meta-data blocks • Directory blocks, indirect-pointer blocks • Problem: Data blocks are overloaded type • Block in “data” region could be: file data, dir, pointer • Direct classification necessary but not sufficient • Indirect classification via inode snooping

  16. SDS Directory Directory Hash Table Type Size Inode Ptr1 Ptr2 Ptr3 Data I-Bit I-Bit D-Bit D-Bit Inode Super Data Inode Indirect Classification: Directories Ptr1 Ptr3 Ptr2

  17. SDS Directory Hash Table Data I-Bit I-Bit D-Bit D-Bit Inode Super Data Inode Indirect Classification In Action Check Hash If Present, Cache Ptr1 Ptr3 Ptr2

  18. Indirect Classification: Issues • Space overhead • Small overhead per directory and indirect block • Time overhead • 1 hash update per pointer, 1 lookup per data block • Tricky: Sometimes data block is seen “early” • Haven’t yet seen pointer associated with data block • Solution #1: OK to misclassify some blocks for some amount of time • Solution #2: Must defer classification until pointer has been observed

  19. Getting Rid Of The Dead • If file blocks are deleted, remove them from cache • No need to keep dead blocks around • Problem: How to determine if a file is deleted? • Need to look for signs of deletion • Three different places to look: • Inode bitmaps • Directory that contains file • Inode itself • Operation inferencing via block differencing

  20. SDS = I-Bitmap Read Old Version Data I-Bit I-Bit D-Bit D-Bit Inode Super Data Inode Operation Inferencing: Detecting Deletes (Inode Bitmap) Diff Result:Deleted Files

  21. Operation Inferencing: Overheads • Space overhead • Block cache of inodes, indirect pointers, bitmaps, etc.(could be substantial) • Time overhead • CPU: Difference operation is like an extra copy • Disk: May require block read (if small/no cache) • [In paper: Quantified time and space overheads] • Main point: There is a CPU and memory cost

  22. Using Semantic Knowledge • Fast RAID Reconstruction • Only copy “live” data to hot-spare • Track-aligned Extents [Schindler et. al. ‘02] • Placing files in disk cognizant manner • Journaling [Hagmann ‘87] • Limit study: can implement complex “FS”-likefunctionality within a semantically-smart disk • File-aware Caching • Caching meta-data under BSD FFS • Caching journal under Linux ext3

  23. Conclusions

  24. Conclusions • Innovation in traditional storage stack is limited • File system: high but not low-level info • Storage system: low but not high-level info • Semantically-smart disks: Best of both worlds? • Takes advantage of “smart” disk systems • Exploit low-level information… • …with high-level knowledge of file system • A remaining challenge • Overcoming the “file system obfuscation” problem

  25. “To know that we know what we know, • and that we do not know what we do not know, • that is true knowledge.” • Confucius • http://www.cs.wisc.edu/wind

  26. “A man cannot inquire about what he knows, • because he knows it, • and in that case he is in no need of inquiry, • nor again can he inquire about • what he does not know, • since he does not know what he is to inquire.” • Socrates

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