COT 5611 Operating Systems Design Principles Spring 2014 Dan C. Marinescu Office: HEC 304 Office hours: M-Wd 3:30 – 5:30 PM

Lecture 4 Reading assignment: the class notes “Distributed systems-basic concepts” available online. 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. 11/13/2018 Lecture 4

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 11/13/2018 Lecture 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. 11/13/2018 Lecture 4

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 11/13/2018 Lecture 4

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 11/13/2018 Lecture 4 6

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) 11/13/2018 Lecture 4 7

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 11/13/2018 Lecture 4 8

Access type; access time Sequential access Tapes CD/DVD Random access devices Disk Seek Search time Read/Write time RAM 11/13/2018 Lecture 4 9

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 11/13/2018 Lecture 4 10

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 11/13/2018 Lecture 4 11

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 11/13/2018 Lecture 4 12

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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. 11/13/2018 Lecture 4 14