CS 620 Comparative Operating Systems Interfaces

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CS 620 Comparative Operating Systems Interfaces

• Professor Timothy Arndt
• BU 331

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Operating Systems Review

• An operating system is a program which is
  interposed between users and the hardware of a
  system
• An operating system can also be seen as a manager
  of resources (e.g. processes, files and I/O
  devices)
• Examples include Windows 98, Windows 2000, Mac OS
  9, Palm OS, and various varieties of UNIX (HP-UX,
  Linux, AIX, etc.)

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The Place of Operating Systems
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Early Operating Systems

• Early computers were controlled directly by a
  programmer or computer operator who entered a job
  (given on a deck of punched cards) and collected
  the output (from a line printer).
• Groups of jobs were placed together in a single
  deck giving rise to batch systems.
• In order to minimize wasted time, a program
  called an operating system was developed. The
  program was always in the computers memory and
  controlled the execution of the jobs.

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Early Operating Systems
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Batch Operating Systems

• In a batch system, various types of cards were
  put together in a deck
• Job control cards contained cards often
  distinguished by a particular character in the
  first row, column position. These cards contained
  instructions for the OS written in the machines
  job control language (JCL)
• Program source code (in a language such as
  FORTRAN) were compiled into an executable form.
• Data cards contained the data needed for a run of
  the program.

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Batch Operating Systems
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Multiprogramming System

• These systems were inefficient since the CPU was
  idle while a running program waited for (e.g.) a
  slow I/O operation to finish.
• In order to get around this problem, several jobs
  were kept in memory, and when the running program
  was blocked waiting for I/O, the OS switched to
  one of the other jobs. This type of system is
  called a multiprogramming system.
• Note that this type of system is still not
  interactive.The user must wait for his job to
  finish before he sees the output.

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Multiprogramming System
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Timesharing systems

• As time went on, users were connected to the CPU
  via terminals, and the switching between jobs was
  fast enough that each user had the illusion of
  being the sole user of the system (if the system
  wasnt overloaded!). This type of system is
  called a timesharing system.
• In this type of system the OSs scheme for
  control of the CPU must be much more complicated.
  In general, each job consists of one or more
  processes.
• Processes can create other processes called child
  processes.

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Processes
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Processes

• A running process consists of several segments in
  the computers main memory.
• The text segment contains the processes
  executable machine instructions.
• The global segment contains global and static
  (variables declared in a procedure whose value
  doesnt change between invocations of the
  procedure) variables.
• The data segment (or heap) contains dynamically
  allocated memory.
• The stack contains activation records for
  subprograms. The activation records contain local
  variables, parameters, return location, etc. When
  a subprogram is called an activation record is
  pushed on the stack. When a subprogram exits,
  its record is popped off the stack.

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A Running Process
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Processes

• Each process has its own virtual address space.
  The size of the space depends on the word size of
  the computer.
• The virtual address space is in general larger
  than the computers physical memory, so some
  virtual memory scheme is needed.
• The OS ensures the virtual to physical mapping
  for each process and also that each process can
  only access memory locations in its own address
  space.

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File System

• Another important resource that the OS manages is
  the set of files that programs access.
• The file system is typically structured as a tree
  in which leaf nodes are files and interior nodes
  are directories.
• Even if files are on separate physical devices,
  they can be combined in a single virtual
  hierarchy.
• The command used to add a new subtree (on a
  separate physical device) to the file system is
  called mount.
• A single file (or directory) can be placed in
  multiple directories without copying the file by
  linking the file. A link is a special type of
  file.

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File System
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Virtual File Hierarchy
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Interprocess Communication

• Separate processes can communicate with each
  other using an OS provided service called
  Interprocess Communication (IPC).
• UNIX processes can use sockets or pipes to
  establish communication with other processes.
• IPC and process spawning are relatively slow,
  leading to the idea of light-weight processes or
  threads in many modern OSs.
• Threads spawned by the same process can
  communicate through shared memory.

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Interprocess Communication
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User vs. Kernel Mode

• In order to make the system more stable, many OSs
  distinguish between processes operating in user
  mode versus those operating in kernel mode.
• User mode processes can access only their memory
  locations in their own address space, cannot
  directly access hardware, etc. Kernel mode
  processes have no such restrictions.
• The fewer processes which run in kernel mode, the
  more robust the system should be. On the other
  hand, mode switching slows down the system.

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User vs. Kernel Mode
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Other OS Requirements

• Besides controlling files, processes and IPC, an
  OS has several other important tasks
• Controlling I/O and other peripheral devices
• Networking
• Security and access control for the various
  resources
• Processing user commands

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Introduction to Distributed Systems

• Distributed systems (as opposed to centralized
  systems) are composed of large numbers of CPUs
  connected by a high-speed network.
• A distributed system is a collection of
  independent computers that appear to the users of
  the system as a single computer.
• Advantages of distributed systems
• Microprocessors offer a better price/performance
  ratio than mainframes.
• A distributed system may have more total power
  than a mainframe.

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Introduction to Distributed Systems

• Some applications involve spatially separated
  machines.
• If one machine crashes, the system as a whole can
  still survive.
• Computing power can be added in small increments.
• Advantages of distributed systems over PCs
• Allow many users access to a common data base.
• Allow many users to share expensive peripherals
  like color printers.
• Make a human-to-human communication easier (e.g.
  by electronic mail)

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Introduction to Distributed Systems

• Spread the workload over the available machines
  in the most cost effective way.
• Disadvantages of distributed systems
• Little software exists at present for distributed
  systems.
• The network can saturate or cause other problems.
• Easy access also applies to secret data.

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Classification of Multiple CPU Systems

• Distributed systems are multiple CPU systems (as
  are parallel systems - we dont distinguish
  between these two).
• In order to compare various multiple CPU systems,
  we would like a classification.
• There is no completely satisfactory
  classification. The most well-known (but now
  outdated) is due to Flynn
• MIMD
• Multiprocessor (shared memory)
• Multicomputer (no shared memory)

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Introduction to Distributed Systems

• SIMD (Single Instruction Multiple Data Stream)
• SISD (Single Instruction Single Data Stream)
  traditional computers.
• MISD (Multiple Instruction Stream Single Data
  Stream) No known examples.
• Each of these categories can further be
  characterized as either
• bus or
• switch
• tightly coupled or
• loosely coupled

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Bus-Based Multiprocessors

• Bus-based multiprocessors consist of some number
  of CPUs all connected to a common bus, along with
  a memory module.
• A typical bus has 32 or 64 address lines, 32 or
  64 data lines, and 32 or more control lines, all
  operating in parallel.
• Since there is just one memory, if one CPU writes
  a word of memory, and another CPU immediately
  reads that word, the value read will be that
  written.
• The memory is said to be coherent.
• This configuration soon causes the bus to be
  overloaded.

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Bus-Based Multiprocessors

• The solution to this problem is to add a
  high-speed cache memory between the CPU and the
  bus.
• The cache holds the most recently accessed words.
  All memory request go through the cache.
• The probability that a requested word is found in
  the cache is called the hit rate.
• If the hit rate is high, the bus traffic will be
  dramatically reduced.

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Bus-Based Multiprocessors

• The use of a cache gives rise to the cache
  coherence problem.
• One solution is the use of a write-through cache.
• The caches must also the monitor the bus and
  invalidate cache entries when writes to that
  address occur.
• This process is called snooping.
• Most bus-based multiprocessors use these
  techniques.

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Bus-Based Multiprocessors

• Facts about caches
• They can be write through, when the processor
  issues a store the value goes in the cache and
  also is sent to memory
• They can be write back, the value only goes to
  the cache.
• In this case, the cache line is marked dirty and
  when it is evicted it must be written back to
  memory.
• Because of the broadcast nature of the bus it is
  not hard to design snooping caches that maintain
  consistency.

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Bus-Based Multiprocessors

• Bus-based multiprocessors are also called
  Symmetric Multiprocessors (SMPs) and they are
  very common.
• Disadvantage (this is really a limitation)
• Cannot be used for a large number of processors
  since the bus bandwidth grows with the number of
  processors and this gets increasingly difficult
  and expensive to supply.
• Moreover the latency grows as the number of
  processors for both speed of light and more
  complicated (electrical) reasons.

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Symmetric Multiprocessors
Processor
Processor
Processor
Processor
Memory
I/O
LAN
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Two Non-SMP Multiprocessors

Processor
Processor
Private Memory
Private Memory
Memory
I/O
LAN
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Two Non-SMP Multiprocessors

Processor
Processor
Memory
I/O
LAN
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Switched Multiprocessors

• To build a multiprocessor with more than (say) 64
  processors, a different method is needed to
  connect the CPUs with the memory.
• One interconnection method is the use of a
  crossbar switch in which each CPU is connected to
  each interleaved bank of memory.
• This method requires n2 crosspoint switches for n
  memories and CPUs, which can be expensive for a
  large n.

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Switched Multiprocessors
M
M
M
M
CPU
CPU
CPU
CPU
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Switched Multiprocessors

• The omega network is an example of a multistage
  network which requires a smaller number of
  switches - (nlog2n)/2 with log2n switching
  stages.
• The number of stages slows down memory access,
  however.
• Another alternative is the use of hierarchical
  systems called NUMA (NonUniform Memory Access).
• Each CPU accesses its own memory quickly, but
  everyone elses more slowly.

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A CC-NUMA

Proc 1
Proc 2
Proc 4
Proc 3
D
D
cache
cache
cache
cache
Memory 0
Memory 1
I/O
I/O
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NUMA

• CC-NUMAs (Cache Coherent NUMAs) are programmed
  like SMPs but to get good performance
• must try to exploit the memory hierarchy and have
  most references hit in your local cache
• most others must hit in the part of the shared
  memory in your "node (CPUs on the local bus).
• NC-NUMAs (Non Coherent NUMAs) are still harder to
  program as you must maintain cache consistent
  manually (or with compiler help).

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Bus-Based Multicomputers

• Multicomputers (with no shared memory) are much
  easier to build (i.e. scale much more easily).
• Each CPU has a direct connection to its own local
  memory.
• The only traffic on the interconnection network
  is CPU-to-CPU, so the volume of traffic is much
  lower.
• The interconnection can be done using a LAN
  rather than a high-speed backplane bus.

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Bus-Based Multicomputers

• In some sense all the computers on the internet
  form one enormous multicomputer.
• The interesting case is when there is some
  closer cooperation between processors say the
  workstations in one distributed systems research
  lab cooperating on a single problem.
• Application must tolerate long-latency
  communication and modest bandwidth, using current
  state-of-the-practice.

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Switched Multicomputers

• The final class of systems are switched
  multicomputers.
• Various interconnection networks have been
  proposed and built. Examples are grids and
  hypercubes.
• A hypercube is an n-dimensional cube. For an
  n-dimensional hypercube, each CPU has n
  connections to other CPUs.
• Hypercubes with 1000s of CPUs (Massively Parallel
  Processors or MPPs) have been available for
  several years.

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Network Operating Systems

• Network operating systems allow one or machines
  on a LAN to serve as file servers which provide a
  global file system accessible from all
  workstations.
• An example of the use of a file server is NFS
  (Network File System).
• The file server receives requests from nonserver
  machines called clients, to read and write files.
• It is possible that the machines all run the same
  OS, but it is not required.

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Network Operating Systems

• A situation like this, where each machine has a
  high degree of autonomy and there are few
  system-wide requirements is known as a network
  operating system.
• It is apparent to the users such a system
  consists of numerous computers.
• There is no coordination among the computers,
  except that the client-server traffic must obey
  the systems protocols.
• The next step up consists of tightly-coupled
  software on the same loosely-coupled hardware.

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True Distributed Systems

• The goal of such a system is to create the
  illusion that the entire network of computers is
  a single timesharing system.
• The characteristics of a distributed system
  include
• A single, global IPC mechanism
• A global protection scheme
• Homogeneous process management
• A single set of system calls
• A homogeneous file systems
• Identical kernels on all CPUs

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True Distributed Systems

• A global file system
• Multiprocessor timesharing systems consist of
  tightly-coupled software on tightly-coupled
  hardware.
• The key character of this class of system is the
  existence of a single run queue.
• Ready to run processes can be run on any of the
  CPUs of the system.
• The operating system in this type of organization
  normally maintains a traditional file system.

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Design Issues

• The single most important issue is the
  achievement of transparency.
• There are several types of transparency that we
  might try to achieve
• Location transparency users cannot tell where
  resources are located.
• Migration transparency resources can move at
  will without changing names.
• Replication transparency users cannot tell how
  many copies exist.

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Design Issues

• Concurrency transparency multiple users can
  share resources automatically.
• Parallelism transparency activities can happen
  in parallel without users knowing.
• The second key design issue is flexibility.
• Flexibility can be provided by a microkernel (as
  opposed to a monolithic kernel) which provides
  just
• An IPC mechanism.
• Some memory management.
• A small amount of low-level process management
  and scheduling.
• Low-level input/output.

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Design Issues

• All other OS services are implemented as
  user-level services
• file system
• directory system
• full process management
• system call handling
• This leads to a highly modular approach in which
  new services are easily added without stopping
  the system and booting a new kernel.
• Services can also be substituted with customized
  services.

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Design Issues

• In a uniprocessor system, the monolithic kernel
  may have a performance advantage (no context
  switches). However in a distributed system, the
  advantage is less.
• Another design goal for distributed systems is
  reliability.
• One aspect of reliability is availability, or
  uptime. This can be improved by exploiting
  redundancy.
• Another aspect is security. This issue is even
  more difficult in distributed systems then in
  uniprocessor systems.

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Design Issues

• A final issue of reliability is fault tolerance.
• Performance in distributed systems is a critical
  issue due to the slow communication times.
• We can attempt to increase the performance by
  selecting the correct grain size of computations.
• Jobs which involve fine-grained parallelism will
  necessarily spend a large amount of time on
  message passing. They are poor candidates for
  distributed systems.
• Jobs that involve large computations and low
  interaction - coarse-grained parallelism - are
  better bets for distributed systems.

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Design Issues

• Scalability is another critical issue.
• Scalability can be achieved by avoiding
• Centralized components
• Centralized tables
• Centralized algorithms
• Decentralized algorithms have the following
  characteristics
• No machine has complete information about the
  system state.
• Machines make decisions based only on local
  information.

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Design Issues

• Failure of one machine does not ruin the
  algorithm.
• There is no implicit assumption that a global
  clock exists.