1. Introduction to Distributed Systems

1. Introduction Two advances in computer technology: A. The development of powerful microprocessors. B. The invention of high-speed computer networks.

The advances make it possible to put together computing systems composed of large numbers of CPUs connected by a high-speed network. They are called distributed systems.

What is a distributed system? A distributed system is a collection of independent computers that appear to the users of the system as a single computer. Eg. 1 a network of workstations in a university or company department. Eg. 2 a factory full of robots, each containing a powerful computer for handling vision, planning, communication, and other tasks. Eg. 3 a large bank with hundreds of branch offices all over the world.

What is a centralized system? A centralized system (or a single- processor system) consists of a single CPU, its memory, peripherals, and some terminals.

Advantages of Distributed Systems over Centralized Systems EconomicsMicroprocessors offer a better price/performance than mainframes SpeedA distributed system may have more total computing power than a mainframe Inherent distribution Some applications involve spatially separated machines ReliabilityIf one machine crashes, the system as a whole can still survive Incremental growth Computing power can be added in small increments

Advantages of Distributed Systems over Independent PCs Data sharingAllow many users access to a common data base Device sharingAllow many users to share expensive peripherals like color printers CommunicationMake human-to-human communication easier, for example, by electronic mail FlexibilitySpread the workload over the available machines in the most cost effective way

Disadvantages of Distributed Systems SoftwareLittle software exists at present for distributed systems NetworkingThe network can saturate or cause other problems SecurityEasy access also applies to secret data

Multiple CPU computer system categories SISD: a computer with a single instruction stream and a single data stream. e.g. all traditional uniprocessor computers (those having only one CPU), from personal computers to large mainframes. SIMD: single instruction, multiple data stream. e.g. array processors with one instruction unit that fetches an instruction, and then commands many data units to carry it out in parallel, each with its own data.

MISD: multiple instruction stream, single data stream. e.g. no known computers fit this model. MIMD: multiple instruction stream, multiple data stream. e.g. a group of independent computers, each with its own program counter, program, and data.

Parallel and distributed computers Hardware Multiprocessors (shared memory) Multicomputers (private memory) Bus Switched Bus Switched Tightly coupledLoosely coupled Sequent, Encore Ultracomputer, RP3 Workstations on a LAN Hypercube, Transputer MIMD

Tightly-coupled system: the delay experienced when a message is sent from one computer to another is short, the data rate is high. Loosely-coupled system: the delay is large and the data rate is low.

Bus-Based Multiprocessors CPU Cache CPU Cache CPU Cache Memory Bus

Drawback As few as 4 or 5 CPUs, the bus will be overloaded. Solution: cache memory. Problem with cache: incoherent. Solution to incoherent: snoopy write through cache.

Write through: whenever a word is written to the cache, it is written through to memory as well. Snoopy cache: a cache is always “snooping” on the bus. Whenever it sees a write occurring to a memory address present in its cache, it either invalids the entry or updates it.

Switched Multiprocessors- crossbar switch MMMM C C C C Crosspoint switch CPUs Memories

Cross switch Advantage: many CPUs can be accessing memory at the same time. Disadvantage: need N 2 crosspoint switches with n CPUs and n memories. One solution: use omega network.

Switched Multiprocessors-omega switch C C C C M M M M 2 X 2 switch An omega switching network

Omega network With n CPUs and n memories, it requires log 2 n switching stages, each containing n/2 switches, for a total of (n log 2 n)/2 switches. Better than crossbar switch, but still big. Another drawback: delay (due to the number of stages).

NUMA machine To reduce delay, use NUMA (NonUniform Memory Access): Some memory is associate with each CPU. Each CPU can access its own local memory quickly, but accessing anybody else’s memory is slower.

NUMA machine Advantage: have better average access times than omega machines Disadvantage: the placement of the programs and data becomes complicated because most access should go to the local memory.

Bus-Based Multicomputers Local memory CPU Local memory CPU Local memory CPU Workstation Network A multicomputer consisting of workstations on a LAN

Switched Multicomputers- Grid

Switched Multicomputers- Hypercube

Loosely-coupled software on loosely-coupled hardware Network Operating Systems: A network of workstations connected by a LAN.

Tightly-coupled software on loosely-coupled hardware True distributed systems: It is tightly- coupled software on the same loosely- coupled (multicomputer) hardware.

Characteristics of a distributed systems There must be a single, global interprocess communication mechanism so that any process can talk to any other process. Process management must also be the same everywhere. The file system must look the same everywhere, too. It is normal that identical kernels run on all the CPUs in the system. Each kernel can have considerable control over its own local resources.

Tightly-coupled software on tightly-coupled hardware Multiprocessor Timesharing Systems The key characteristic of this class of system is the existence of a single run queue: a list of all the processes in the system that are logically unblocked and ready to run.

Comparison Network OS Distributed OSMultiprocessor OS Does it look like a virtual uniprocessor? NoYes Do all have to run the same operating system? NoYes How many copies of the operating system are there? NN1 How is communication achieved?Shared files MessagesShared memory Are agreed upon network protocols required? Yes No Is there a single run queue?No Yes Does file sharing have well-defined semantics? Usually NoYes

Design Issues-Transparency Location transparencyThe users cannot tell where resources are located Migration transparencyResources can move at will without changing their names Replication transparencyThe users cannot tell how many copies exist Concurrency transparencyMultiple users can share resources automatically Parallelism transparencyActivities can happen in parallel without users knowing

Design Issue - Flexibility one school maintains that each machine should run a traditional kernel that provides most services itself. The other maintains that the kernel should provide as little as possible, with the bulk of the operating system services available from user-level servers.

Design Issue - Reliability High availability Security Fault tolerance

Design Issue - performance Fine-grained parallelism: jobs that involve a large number of small computations, especially ones that interact highly with one another, may cause trouble on a distributed system with relatively slow computation. Coarse-grained parallelism: jobs that involve large computations, low interaction rates, and little data.

Design Issue - Scalability Potential bottlenecks that designers should try to avoid in very large distributed systems. Centralized componentsA single mail server for all users Centralized tablesA single on-line telephone book Centralized algorithmsDoing routing based on complete information