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(Architectural Support for) Semantically-Smart Disk Systems
April 29, 2003 Jarrod Lewis University of Wisconsin-Madison
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Objectives Semantically-Smart Disk Systems (SDS)
“Disk processing” for SDS Architecture brainstorm 11/29/2018 Jarrod A. Lewis
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Overview: Motivation Observe: storage systems important
Want better storage! Problem: fixed interfaces Hard to change OS, file systems Solution: innovate around interfaces Infer information 11/29/2018 Jarrod A. Lewis
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Overview: Approach Where to innovate? The semantic gap
At lowest level (disks) The semantic gap Infer higher level “semantic” information Exploit in lower levels Semantically-Smart Disk Systems (SDS) Reverse engineer disk traffic E.g, Distinguish meta-data from data Handle types differently 11/29/2018 Jarrod A. Lewis
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Overview: Applications
Improve performance Smarter layout Smarter file caching Improve availability D-GRAID RAID that degrades gracefully Structural caching Explicit journaling of metadata Improve security Secure delete 11/29/2018 Jarrod A. Lewis
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Overview: Issues Traditional RAID processing SDS: an evolving workload
Parity calculation Simple prefetching SDS: an evolving workload Block differencing Bitwise ‘diff’ between 4kB chunks of data Hash tables E.g, to distinguish type of (overloaded) data blocks Deferred work Save block movement for “idle” time 11/29/2018 Jarrod A. Lewis
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Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues 11/29/2018 Jarrod A. Lewis
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Motivation Storage critical to useful computer systems
Want improvements! Performance, availability, security, etc… But… OS and storage interfaces lack explicit “hooks” So… Improve storage with “implicit” hooks 11/29/2018 Jarrod A. Lewis
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Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues 11/29/2018 Jarrod A. Lewis
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Approach Reverse engineer disk traffic
Determine semantics Behind narrow interface (SCSI) Build new functionality Block-based interfaces: NOW and LATER SCSI interface lives on iSCSI (SCSI over IP) emerging Processing support? “Data movement” vs. “computation” Block differencing Hash tables 11/29/2018 Jarrod A. Lewis
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Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues 11/29/2018 Jarrod A. Lewis
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Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues 11/29/2018 Jarrod A. Lewis
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SDS Hashing: Space Overheads
Indirect Classification Block-Inode Association Operation Inferencing NetNews 93.3 KB 1.91 MB 105.3 KB PostMark 3.45 KB 936.4 KB 19.9 KB Andrew 360 B 3.54 KB 1.34 KB 11/29/2018 Jarrod A. Lewis
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Block differencing Completely independent computations
SIMD? Vectors? Distribute slices of blocks to multiple processors? Lots of block storage needed How to design memory hierarchy? 11/29/2018 Jarrod A. Lewis
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Hardware hash tables Terrible locality
Bad for traditional memory hierarchies Lots of storage needed What memory structures to use? Distribute hash table? Parallelize lookups Think of disks as multiple cache banks? 11/29/2018 Jarrod A. Lewis
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Deferred work Queue up work (block movements) Buffering overhead?
Wait for idle time Buffering overhead? 11/29/2018 Jarrod A. Lewis
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Other ideas/issues? 11/29/2018 Jarrod A. Lewis
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Thank you for coming. 11/29/2018 Jarrod A. Lewis
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