cs 620 advanced operating systems

CS 620 Advanced Operating Systems

Lecture 1 - Introduction

Professor Timothy Arndt

BU 331

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 XP,

Mac OS X, Palm OS, and various varieties of UNIX (HP-UX, Linux, AIX, etc.)

The Place of Operating Systems

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 computer’s memory and controlled the execution of the jobs.

Early Operating Systems

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 machine’s 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.

Batch Operating Systems

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.

Multiprogramming System

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 wasn’t overloaded!). This type of system is called a timesharing system.

• In this type of system the OS’s 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.

Processes

Processes

• A running process consists of several segments in the computer’s 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 doesn’t 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, it’s record is popped off the stack.

A Running Process

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 computer’s 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.

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.

File System

Virtual File Hierarchy

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.

Interprocess Communication

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.

User vs. Kernel Mode

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

Introduction to Distributed Systems

Distributed systems (as opposed to centralized systems) are composed of large numbers of CPUs connected by a high-speed network.

Definition of a Distributed System

• A distributed system is:

• A collection of independent computers that appears to its users as a single coherent system.


Advantages of 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.

• Allow many users to share expensive peripherals like color printers.

• Spread the workload over the available machines in the most cost effective way.


Disadvantages of distributed systems:• Less software exists for distributed systems.

• The network can saturate or cause other problems.

• Easy access also applies to secret data.

Classification of Multiple CPU Systems

Distributed systems are multiple CPU systems (as are parallel systems - we don’t 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)


• 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

Hardware Concepts

1.6

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.


• A bus-based multiprocessor.

1.7


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.


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.


• 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.


Bus-based multiprocessors are also called Symmetric Multiprocessors (SMPs) and they are very common.

The bus can also connect multiple processors on the same die, leading to Multicore Systems

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.

Symmetric Multiprocessors

Processor ProcessorProcessor Processor

Memory I/O

LAN

Two Non-SMP Multiprocessors

Processor Processor

Memory I/O

LAN

Private Memory

Private Memory

Two Non-SMP Multiprocessors

Processor Processor

Memory I/O

LAN

Dual-core Dual-Processor System

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.


a) A crossbar switchb) An omega switching network

1.8


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 else’s more slowly.

A CC-NUMA

Memory 0 Memory 1I/O I/O

Proc 1 Proc 2 Proc 4Proc 3

cache cachecache cacheD D

NUMA

Production of cc-NUMAs is well-supported by the AMD Opteron (e.g. by SGI).

Other cc-NUMA systems are being built using Intel’s Itanium processor with additional hardware support (e.g. by HP running HP-UX).

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).

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.

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.

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.

Switched Multicomputers

a) Gridb) Hypercube

1-9

Software Concepts

• DOS (Distributed Operating Systems)• NOS (Network Operating Systems)• Middleware

System Description Main Goal

DOSTightly-coupled operating system for multi-processors and homogeneous multicomputers

Hide and manage hardware resources

NOSLoosely-coupled operating system for heterogeneous multicomputers (LAN and WAN)

Offer local services to remote clients

MiddlewareAdditional layer atop of NOS implementing general-purpose services

Provide distribution transparency

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.


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 system’s protocols.

• The next step up consists of tightly-coupled software on the same loosely-coupled hardware.


• General structure of a network operating system.

1-19


• Two clients and a server in a network operating system.

1-20


• Different clients may mount the servers in different places.

1.21

Distributed Operating Systems (DOS)

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

DOS

• 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.

DOS

• General structure of a multicomputer operating system

1.14

Middleware

• Middleware allows heterogeneous systems to achieve the appearance of a single coherent system

• An additional layer is added on top of the NOS services

Middleware

• General structure of a distributed system as middleware.

1-22

Middleware and Openness

• In an open middleware-based distributed system, the protocols used by each middleware layer should be the same, as well as the interfaces they offer to applications.

1.23

Comparison between Systems

ItemDistributed OS

Network OS

Middleware-based OSMultipro

c.Multicomp.

Degree of transparency

Very High High Low High

Same OS on all nodes

Yes Yes No No

Number of copies of OS

1 N N N

Basis for communication

Shared memory

Messages FilesModel specific

Resource management

Global, central

Global, distributed

Per node Per node

Scalability No Moderately Yes Varies

Openness Closed Closed Open Open

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.

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.

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.

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.

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.

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.

Design Issues

• Failure of one machine does not ruin the algorithm.

• There is no implicit assumption that a global clock exists.

Scalability Problems

Examples of scalability limitations.

Concept Example

Centralized services A single server for all users

Centralized data A single on-line telephone book

Centralized algorithmsDoing routing based on complete information

Scaling Techniques (1)

1.4

The difference between letting:

a) a server or

b) a client check forms as they are being filled

Scaling Techniques (2)

1.5

An example of dividing the DNS name space into zones.

New Distributed Systems Architectures

• Cluster Computing

• Grid Computing

• Cloud Computing

• Mobile Ad Hoc Network (MANET)

• Wireless Sensor Network

• Peer-to-Peer Network

cs 620 advanced operating systems

Documents

type of system

system wasnt

running program

data cards

operating systems reviewan

child processes

computers memory

deckjob control cards