1. COT 5611 Operating Systems Design Principles Spring 2012
Dan C. Marinescu
Office: HEC 304
Office hours: M-Wd 5:00-6:00 PM

2. Lecture 4 – Monday January 23
Reading assignment: the class notes “Distributed systems-basic concepts” available online.
Phase 0 projects were due last Thursday!!
Last time
Computers as a distinct species of complex systems
Milestones in the evolution of computing and communication technology.
Factors affecting the complexity of computing and communication systems
The software
The exponential growth
Coping with complexity
Resource sharing and complexity
Scale-free systems or how nature deals with complexity.
Lessons learned.
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Lecture 4

3. Today Names and fundamental abstractions Parallel systems The speedup
Parallelism
Bit-level parallelism
Instruction-level parallelism
Data parallelism
Task-parallelism
Parallel architectures: SISD, SIMD, MIMD
Distributed systems
Transparency (Access, Location, Concurrency, Replication, Failure, Performance, Scaling).
Communication in distributed systems
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4. Naming
Modularity along with abstraction, layering, and hierarchy allow a designer to cope with complexity;
Names and addresses  provide the means to connect modules.
A system  a bunch of resources, glued together with names
Naming allows the designer to:
Delay the implementation of some modules; use dummy ones
Replace an implementation with another one.
Binding choosing an implementation for a module
Delayed binding; use a place holder.
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Lecture 4

5. Names and fundamental abstractions
The fundamental abstractions
Storage  mem, disk, data struct, file dystems, disk arrays
Interpreters  cpu, programming language e.g. java VM
Communication wire, Ethernet
Names are critical for all three abstractions – how could otherwise the components interact with one another.
Naming:
Flat
Hierarchical
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6. Names and the three basic abstractions
Memory  stores named objects
write(name, value) value  READ(name)
file system: /dcm/classes/Fall09/Lectures/Lecture5.ppt
Interpreters  manipulates named objects
machine instructions ADD R1,R2
modules  Variables call sort(table)
Communication Links connect named objects
HTTP protocol used by the Web and file systems
Host: boticelli.cs.ucf.edu
put /dcm/classes/Fall09/Lectures/Lecture5.ppt
get /dcm/classes/Fall09/Lectures/Lecture5.ppt
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7. Memory Hardware memory: Devices RAM (Random Access Memory) chip
Flash memory  non-volatile memory that can be erased and reprogrammed
Magnetic tape
Magnetic Disk
CD and DVD
Systems
RAID
File systems
DBMS (Data Base management Systems)
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8. Attributes of the storage medium/system
Durability  the time it remembers
Stability  whether or not the data is changed during the storage
Persistence  property of data storage system, it keeps trying to preserve the data
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9. Access type; access time
Sequential access
Tapes
CD/DVD
Random access devices
Disk
Seek
Search time
Read/Write time
RAM
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10. Physical memory organization
RAM  two dimensional array. To select a flip-flop provide the x and y coordinates.
Tapes  blocks of a given length and gaps (special combination of bits.
Disk:
Multiple platters
Cylinders correspond to a particular position of the moving arm
Track  circular pattern of bits on a given platter and cylinder
Record  multiple records on a track
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11. Names and physical addresses
Location addressed memory  the hardware maps the physical coordinates to consecutive integers, addresses
Associative memory  unrestricted mapping; the hardware does not impose any constraints in mapping the physical coordinates
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12. Critical properties of a storage medium/system
Read/Write Coherence  the result of a READ of a memory cell should be the same as the most recent WRITE to that cell.
Before-or-after atomicity the result of every READ or WRITE is as if that READ or WRITE occurred either completely before or completely after any other READ or WRITE
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13. 11/13/2018
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14. Why it is hard to guarantee the critical properties?
Concurrency  multiple threads could READ/WRITE to the same cell
Remote storage  The delay to reach the physical storage may not guarantee FIFO operation
Optimizations  data may be buffered to increase I/O efficiency
Cell size may be different than data size  data may be written to multiple cells.
Replicated storage  difficult to maintain consistency.
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15. See the class notes for the parallel and distributed systems topics
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