COMP 206: Computer Architecture and Implementation

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COMP 206Computer Architecture and Implementation

• Montek Singh
• Mon., Nov. 25, 2002
• Topic Storage Systems (Disk Technology) contd.

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Ensembles of Disks

• Key idea
• Use collection of disk drives to improve
  characteristics of disk systems (storage
  capacity, bandwidth, etc.)
• Used in mainframes for a long time
• RAID
• Redundant Array of Inexpensive Disks (original
  1988 acronym)
• Redundant Array of Independent Disks (redefined
  in 1992)

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Improving Bandwidth with Disk Arrays

• Arrays of independent disk drives
• Similar to high-order interleaving in main
  memories
• Each file assigned to different disk drive
• Simultaneous access to files
• Load balancing issues
• File striping/disk striping/disk interleaving
• Single file distributed across array of disks
• Similar to low-order interleaving in main
  memories
• Each logical I/O request corresponds to a data
  stripe
• Data stripe divided into number of equal sized
  stripe units
• Stripe units assigned to different disk units
• Two kinds of striping depending on size of stripe
  unit
• Fine-grained striping Stripe unit chosen to
  balance load
• Coarse-grained striping Larger stripe unit

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Improving Availability with Disk Arrays

• Failure rates of Disk Arrays can be quite high
• MTTF of large-system disks approaches 1,000,000
  hours
• MTTF of PC-class disks approaches 150,000 hours
• But, array of 1,000 PC-class disks has MTTF of
  150 hours
• All schemes to cope with low MTTF aim to fail
  soft
• Operation should be able to continue while repair
  is made
• Always depends on some form of redundancy

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RAID-0

• Striped, non-redundant
• Parallel access to multiple disks
• Excellent data transfer rate (for small strips)
• Excellent I/O request processing rate (for large
  strips)
• Typically used for applications requiring high
  performance for non-critical data

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RAID-1

• Mirrored/replicated (most costly form of
  redundancy)
• I/O request rate good for reads, fair for writes
• Data transfer rate good for reads writes
  slightly slower
• Read can be serviced by the disk with the shorter
  seek distance
• Write must be handled by both disks
• Typically used in system drives and critical
  files
• Banking, insurance data
• Web (e-commerce) servers

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Combining RAID-0 and RAID-1

• Can combine RAID-0 and RAID-1
• Mirrored stripes (RAID 01, or RAID 01)
• Example picture above
• Striped Mirrors (RAID 10, or RAID 10)
• Data transfer rate fair for reads and writes
• Reliability good
• Efficiency poor (100 overhead in terms of disk
  utilization)

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RAID-3

• Fine-grained (bit) interleaving with parity
• E.g., parity sum modulo 2 (XOR) of all bits
• Disks are synchronized, parity computed by disk
  controller
• When one disk fails (how do you know?)
• Data is recovered by subtracting all data in good
  disks from parity disk
• Recovering from failures takes longer than in
  mirroring, but failures are rare, so is okay
• Hot spares used to reduce vulnerability in
  reduced mode
• Performance
• Poor I/O request rate
• Excellent data transfer rate
• Typically used in large I/O request size
  applications, such as imaging or CAD

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RAID-2

• Hamming codes capable of correcting two or more
  erasures
• E.g., single error-correcting, double
  error-detecting (SEC-DED)
• Problem with small writes (similar to DRAM cycle
  time/access time)
• Poor I/O request rate
• Excellent data transfer rate

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RAID-4

• Coarse-grained striping with parity
• Unlike RAID-3, not all disks need to be read on
  each read
• New parity computed by computing difference
  between old and new data
• Drawback
• Like RAID-3, parity disk involved in every write
  serializes small reads
• I/O request rate excellent for reads, fair for
  writes
• Data transfer rate fair for reads, fair for
  writes

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RAID-5

• Key Idea reduce load on parity disk
• Block-interleaved distributed parity
• Multiple writes can occur simultaneously
• Block 0 can be accessed in parallel with Block 5
• First needs disks 1 and 5 second needs disks 2
  and 4
• I/O request rate excellent for reads, good for
  writes
• Data transfer rate good for reads, good for
  writes
• Typically used for high request rate,
  read-intensive data lookup

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Removable Media

• Magnetic Tapes
• Have been used in computer systems as long as
  disks
• Similar magnetic technology as disks
• have followed similar density improvements as
  disks
• Long strips wound on removable spools
• Benefits can be essentially of unlimited
  length removable
• Drawbacks only offer sequential access wear
  out
• Used for archival backups but on the way out
• Optical Disks CDs and DVDs
• CD-ROM/DVD-ROM removable, inexpensive, random
  access
• CD-R/RW, DVD-R/RAM writable/re-writable
• Becoming immensely popular replacing floppy
  drives, tape drives
• Flash flash cards, memory sticks, digital film
• Microdrives small portable hard disks (up to
  1GB)

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Interfacing I/O Subsystem to CPU

• Where do we connect I/O devices?
• Cache?
• Memory? ?
• Low-cost systems I/O bus memory bus!
• CPU and I/O compete for bus
• How does CPU address I/O devs.?
• Memory-mapped I/O
• Portions of address space assigned to I/O devices
• I/O opcodes (not very popular)
• How does CPU synch with I/O?
• Polling vs. interrupt-driven
• Real-time systems hybrid
• Clock interrupts periodically
• CPU polls during interrupt

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Does I/O Performance Matter?

• The No Argument
• There is always another process to run while one
  process waits for I/O to complete
• Counter-arguments
• Above argument applies only if throughput is sole
  goal
• Interactive software and personal computers lay
  more emphasis on response time (latency), not
  throughput
• Interactive multimedia, transaction processing
• Process switching actually increases I/O (paging
  traffic)
• Desktop/Mobile computing only one
  person/computer ? fewer processes than in
  time-sharing
• Amdahls Law benefits of making CPU faster
  taper off if I/O becomes the bottleneck

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Does CPU Performance Matter?

• Consequences of Moores Law
• Large, fast CPUs
• Small, cheap CPUs
• Main goal keeping I/O devices busy, not keeping
  CPU busy
• bulk of the hardware cost is in I/O peripherals,
  not CPU
• Shift in focus
• From computation to communication
• Reflected in change of terminology
• 1960s-80s Computing Revolution
• 1990s-present Information Age

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Does Performance Matter?

• Performance is not the problem it once was!
• 15 years of doubling CPU speed every 18 months
  (x1000)
• Disks also have steadily become bigger and faster
• Most people would prefer more reliability than
  speed
• Todays speeds come at a cost frequent crashes
• Program crashes ? frustration
• Disk crashes ? hysteria
• Reliability, availability, dependability, etc.
  are the key terms
• Client-server model of computing has made
  reliability the key criterion for evaluation
• E.g., UNC-COMPSCI IMAP server 300 MHz or
  something, 99.9 uptime