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Paper by: Chris Ruemmler and John Wikes Presentation by: Timothy Goldberg, Daniel Sink, Erin Collins, and Tony Luaders. Introduction. Disk Drive performance improvements at 7-10% Compared to microprocessors at 40-60% or disk storage capacities at 60-80% (annually) - PowerPoint PPT Presentation
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Paper by: Chris Ruemmler and John Wikes
Presentation by: Timothy Goldberg, Daniel Sink, Erin Collins, and Tony Luaders
IntroductionDisk Drive performance improvements at 7-
10%Compared to microprocessors at 40-60% or
disk storage capacities at 60-80% (annually)Simulation models to compare alternative
approachesHigh quality disk drive model
Error factor 14 times smaller
OutlineIntroductionCharacteristics of Modern Disk Drives
Recording ComponentsPositioning ComponentsDisk Controller
Modeling Disk Drives
Characteristics of Modern DiskNon-removable magnetic disk drivesContain a mechanism and controller
Recording Components: rotation disks and heads
Positioning Components: moves heads into correct position with track-following system
Emphasis on features that could be important when creating a disk drive model
Recording ComponentsSmaller disks:
Less surface area for dataLess power consumptionCan spin fasterSmaller seek distances
Increased storage density:Better linear recording density, maximum rate of
flux changesPacking separate tracks of data more closely
togetherMay contain from 1 to 12 platters
Stack rotates in lockstep
Recording ComponentsSpindle rotation speed:
Higher spin speed increases transfer rates, shortens rotation latencies
Higher power consumption, requires better bearings
Each platter surface has a disk headResponsible for recording (writing)And sensing (reading) magnetic flux variation
Single Read-Write data channelCan be switched between the headsResponsible for encoding and decoding data stream
into or from a series of magnetic phase changes stored on the disk
Disk Drive
Positioning ComponentsData surfaces are set up to store data in tracksModern disks have about 2,000 cylinders and are
3.5 inches.Cylinder is a single stack of tracks at a common
distance from the spindleTo access the data stored on a track, the disk
arms must rotate all the disks to get the desired track to the disk head.
This system ensures that the track is reached even with interruptionsExternal vibrations, shocks, and disk flaws (non
circular tracks)
SeekingThe speed of head movementFaster seeking requires more power
Half the seek time requires 4x powerSeek is composed of:
Speedup (arm moves until at half seek distance)
Coast (for long seeks, max velocity)Slowdown (rest close to desired track)Settle (puts disk head on desired location)
Track FollowingFine-tuning the head position at the end of
the seek and keeping the head on the desired track
Determines if head is correctly aligned by using positioning information on the disk at manufacturing time
Performs head switchesWhen the controller switches its data channel
from one surface to the next in the same cylinder
Data layoutA disk appears to its client computer as a linear
vector of addressable blocks which are mapped to physical sectors on the disk.
Using this method, the disk can hide bad sectors and do low-level performance optimizations.
Zoning: tracks are longer at the outside of a platter than at the inside.Maximize storage capacity
Track skewing: faster sequential access across track boundariesAllows data to be read or written at nearly full
media speedSparing: stores a list of flaws in the desk surface
to be skipped
The Disk ControllerMediates access to the mechanismRuns the track-following systemTransfers data between the disk drive and
the clientManages an embedded cache
caching of requestsSpeed-matching buffer can be extended to
include some form of caching for both reads and writes.
Caches in disk drives are relatively small because of space limitations.
Read-ahead: faster than seeking if the cache gets a hit
Write caching: saves cache informationCache is volatile, losing its contents if power to the
drive is lostCommand queuing: allows for multiple
outstanding requests at the same timeDisk controller determines the best execution order,
subject to additional host constraints.
Modeling Disk Drives
The Simulator• Based in C++ using a version of the AT&T
tasking library• The Basic ideas are readily applicable to
other simulation environments• The disk drive is modeled as two tasks and
some additional control structures• Task one models the mechanism, including the
head and platter (rotation) positions.• Task two, the direct memory access engine
(DMA), models the SCSI bus interface and its transfer engine.
The Simulator• The cache object buffers requests between
two tasks and is used to manage the asynchronous interactions between the bus interface and the disk mechanism tasks.
• The simulator can process about 2,000 I/Os per second on an HP9000 Series 800 Model H50 system• This allows 1 million requests to be serviced in
approximately 10 minutes
Evaluation• Took week long samples from a longer trace
series of HP-UX (Unix) computer systems. • A metric to evaluate the models used a time
distribution curve for the real drive and the model output and use the root mean square of the horizontal distance between these two curves.
No modeling•Uses a constant fixed time for each I/O•A demerit factor that is 35% of the average I/O time•This model is not good
A simple model•A better model requires:
•A seek time linear with the distance•No head-settle effects or head-switching costs•A rotational delay•A fixed controller overhead•A transfer time linear with the length of request
•demerit of 15% of a mean I/O time
Modeling head-positioning effects•Determined which track and cylinder the request started on and where it ended•Added a fix cost of 2.5 ms for each head and track switch•Demerit of 6.2% of a mean I/O time
Modeling rotation position•Calculate rotational latency by keeping track of rotational position of the disk•Account for spare sectors•A demerit of 2.6% of mean I/O time
Modeling data caching•Uses both read-ahead and immediate reporting•Large disparity due to caching•50% of request are completed in 3ms or less•Demerit of 112% is not acceptable!
Modeling data caching•Added aggressive read-ahead and immediate reporting to the model•Demerit is now only 5.7% of the mean I/O time
Model summary•Careful modeling is neither too difficult nor too costly•A good model needs careful calibration and tuning•These features and others may become particularly important when a workload has large data transfers