RAID COP 5611 Advanced Operating Systems Adapted from Andy Wang’s slides at FSU

Parallel Disk Access and RAID One disk can only deliver data at its maximum rate So to get more data faster, get it from multiple disks simultaneously Saving on rotational latency and seek time

Utilizing Disk Access Parallelism Some parallelism available just from having several disks But not much Instead of satisfying each access from one disk, use multiple disks for each access Store part of each data block on several disks

Disk Parallelism Example open(foo)read(bar)write(zoo) File System

Data Striping Transparently distributing data over multiple disks Benefits –  Increases disk parallelism  Faster response for big requests Major parameters are number of disks and size of data interleaf

Fine-Grained Vs. Coarse-Grained Data Interleaving Fine grain data interleaving +High data rate for all requests  But only one request per disk array  Lots of time spent positioning Coarse-grain data interleaving +Large requests access many disks +Many small requests handled at once  Small I/O requests access few disks

Reliability of Disk Arrays Without disk arrays, failure of one disk among N loses 1/Nth of the data With disk arrays (fine grained across all N disks), failure of one disk loses all data N disks 1/Nth as reliable as one disk

Adding Reliability to Disk Arrays Buy more reliable disks Build redundancy into the disk array  Multiple levels of disk array redundancy possible  Most organizations can prevent any data loss from single disk failure

Basic Reliability Mechanisms Duplicate data Parity for error detection Error Correcting Code for detection and correction

Parity Methods Can use parity to detect multiple errors  But typically used to detect single error If hardware errors are self-identifying, parity can also correct errors When data is written, parity must be written, too

Error-Correcting Code Based on Hamming codes, mostly Not only detect error, but identify which bit is wrong

RAID Architectures Redundant Arrays of Independent Disks Basic architectures for organizing disks into arrays Assuming independent control of each disk Standard classification scheme divides architectures into levels

Non-Redundant Disk Arrays (RAID Level 0) No redundancy at all So, what we just talked about Any failure causes data loss

Non-Redundant Disk Array Diagram (RAID Level 0) open(foo)read(bar)write(zoo) File System

Mirrored Disks (RAID Level 1) Each disk has second disk that mirrors its contents  Writes go to both disks  No data striping + Reliability is doubled + Read access faster - Write access slower - Expensive and inefficient

Mirrored Disk Diagram (RAID Level 1) open(foo)read(bar)write(zoo) File System

Memory-Style ECC (RAID Level 2) Some disks in array are used to hold ECC E.g., 4 data disks require 3 ECC disks + More efficient than mirroring + Can correct, not just detect, errors - Still fairly inefficient

Memory-Style ECC Diagram (RAID Level 2) open(foo)read(bar)write(zoo) File System

Bit-Interleaved Parity (RAID Level 3) Each disk stores one bit of each data block One disk in array stores parity for other disks + More efficient that Levels 1 and 2 - Parity disk doesn’t add bandwidth - Can’t correct errors

Bit-Interleaved RAID Diagram (Level 3) open(foo)read(bar)write(zoo) File System

Block-Interleaved Parity (RAID Level 4) Like bit-interleaved, but data is interleaved in blocks of arbitrary size  Size is called striping unit  Small read requests use 1 disk + More efficient data access than level 3 + Satisfies many small requests at once - Parity disk can be a bottleneck - Small writes require 4 I/Os

Block-Interleaved Parity Diagram (RAID Level 4) open(foo)read(bar)write(zoo) File System

Block-Interleaved Distributed-Parity (RAID Level 5) Sort of the most general level of RAID Spread the parity out over all disks +No parity disk bottleneck +All disks contribute read bandwidth –Requires 4 I/Os for small writes

Block-Interleaved Distributed-Parity Diagram (RAID Level 5) open(foo)read(bar)write(zoo) File System

Where Did RAID Look For Performance Improvements? Parallel use of disks  Improve overall delivered bandwidth by getting data from multiple disks Biggest problem is small write performance But we know how to deal with small writes...