1. (Architectural Support for) Semantically-Smart Disk Systems
April 29, 2003
Jarrod Lewis
University of Wisconsin-Madison

2. Objectives Semantically-Smart Disk Systems (SDS)
“Disk processing” for SDS
Architecture brainstorm
11/29/2018
Jarrod A. Lewis

3. 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

4. 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

5. 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

6. 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

7. Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues
11/29/2018
Jarrod A. Lewis

8. 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

9. Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues
11/29/2018
Jarrod A. Lewis

10. 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

11. Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues
11/29/2018
Jarrod A. Lewis

12. Outline Overview Motivation Approach Semantically-Smart Disk Systems
Architectural Issues
11/29/2018
Jarrod A. Lewis

13. 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

14. 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

15. 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

16. Deferred work Queue up work (block movements) Buffering overhead?
Wait for idle time
Buffering overhead?
11/29/2018
Jarrod A. Lewis

17. Other ideas/issues?
11/29/2018
Jarrod A. Lewis

18. Thank you for coming.
11/29/2018
Jarrod A. Lewis