Introduction. Distributed Systems. Introduction. Introduction. Instructor Brian Mitchell - Brian

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1 Distributed 1 Directory 1 Cache Directory 2 Cache N Directory N Interconnection Network... Cache N N Instructor Brian Mitchell - Brian bmitchel@mcs.drexel.edu Course Information CS721 - Tuesday 6-9 M Online Information lease check course web page several times per week. The web page will be my primary mechanism for communicating: Special and Emergency Information (posted by 12:00 noon on day of the class) Syllabus Assignments Exam Information Solutions to roblems Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 1 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 2 Course Objective Investigate distributed systems with an emphasis on distributed operating systems Review research in the area of distributed systems and distributed systems architecture Textbook None required Distributed Operating by Tannenbaum is optional Selected research papers Additional References References to additional material will be provided as the material is reviewed Homework s, rojects, Exams Assignments & rogramming rojects: Homework's involving the design and implementation of small programs to illustrate distributed systems concepts will be regularly assigned(consult web page). Based on difficulty, you will have 1-2 weeks to complete each assignment. For this course you may develop programming solutions using the Java, C or C++ programming language Midterm and Final: There will be no scheduled exams for this course, however, this may change. Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 3 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 4 1

2 Outline of Topics Grading The following distribution will be used to determine your final grade in this course: 85%: rogramming roject 15%: Research aper resentation olicies All homework and programming assignments are individual efforts, unless specifically stated otherwise in the assignment definition. You may use your colleagues for advice, however, all assignments must be your original work Late assignments will be penalized 10% per week. Makeup exams will take the form of an oral exam or an alternative test (in-class or take-home). Distributed systems Distributed systems architecture Data communications RC Group Communications Scalability Fault Tolerance (Reliability, Availability) Clustering Distributed Synchronization Distributed Shared Cache Coherence Distributed File Distributed Components EJB, CORBA, DCOM Brian Mitchell - Distributed 5 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 6 Teaching Approach We will first cover material pertinent to a distributed systems subject area in lecture When appropriate we will review one or more research papers related to a subject area Whenever possible online copies of the research papers will be provided You may be required to go to the library and photocopy a copy of some papers that I will place on reserve Distributed systems are useful because they offer: Scalability, Reliability, Flexibility/Expandability Distributed system designers must overcome many complex challenges Maintaining distributed time Fault tolerance (Reliability and Availability) Efficient scalability More capacity Correct operation Managing consistency among distributed devices Good performance Generally we want a distributed system to appear as one large non-distributed system from the users perspective Sometimes we want distributed systems to be act as parallel machines to run parallel algorithms Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 7 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 8 2

3 Distributed Distributed Why distributed systems? Since the early days of computers engineers have been able to dramatically improve the price/performance of computer systems How: Advances in hardware technology Software that takes advantage of, and requires powerful hardware Can this trend continue? We are now starting to see the limits of the laws of physics effect the performance of microprocessor designs Not able to send signals to all areas of a chip in a single clock cycle Must add buffers to chips Question: How can engineers continue to scale up hardware designs? Answer: Add multiple processors to computer system designs and allow the processors to work together to improve the overall computing capacity of the computer How: Leverage advances in hardware and network design to enable independent processors to efficiently work together Today most distributed system have very few processors (< 64, but typically < 16) The future distributed systems will have thousands of processors Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 9 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 10 Flavors of Distributed Challenges roprietary Multiple processors connected together using a proprietary bus, network or backplane Networked Use general purpose computers that communicate using standard network technologies Non-proprietary networked distributed systems are now possible by having commercially available high bandwidth LAN and WAN s 1Gbit/sec or better Consider how the Internet can enable a distributed system Example: The Berkley SETI project In the Operating (CS720) course we discussed a rationale for an OS Directly interfacing user programs with hardware is COMLEX Building programs for specific computer architectures is not portable If every program included code to interface with the computer hardware Redundancy Inconsistent quality Inefficient use of resources DESIRE => Shield programmers from the complexity of the hardware OS is a layer that sits on top of the hardware OS provides an interface or virtual macninethat is easy to understand and program Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 11 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 12 3

4 Challenges The challenges for a distributed system are consistent with that of a centralized (nondistributed) system However, distributed systems are more complex then centralized systems Coordination Issues Synchronization Issues Communication Issues Heterogeneity Issues Desire is to have a distributed system architecture and a distributed operating system to handle and abstract these complex tasks Goal: Have systems software (the OS ) handle the complex tasks and provide the user (and programmers) with a simple interface to the distributed system Definition of a Distributed System A distributed system is a collection of independent computers that appear to the users of the system as a single computer Fundamental aspects of the distributed system definition Computers are autonomous (independent) Users think of the system as a single computer Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 13 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 14 Distributed System Example Consider a office where each user has their own computer In addition to each users personal workstation there may be an additional pool of processors that are dynamically assigned to users on an as-needed basis rovides additional processing power on demand Commands can be executed as follows: On the users personal computer On another computer available on the network In parallel on multiple processors that are available on the network Key oint: Enable users to dynamically grow their capacity and execute commands in the most appropriate mode to ensure maximal efficiency and performance Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 15 Distributed Applications There are some applications that inherently lead themselves to be supported by a distributed system Inventory Example Consider a company with many stores Each store keeps a real-time accounting of their current inventory eriodically all of the individual stores inventory needs to be interrogated by the central branch Solution: Make a distributed system where the complete system looks like a single computer to application programs. However each store has its own computer to store and manage its own data for fast access Also allow an individual store to check on the inventory of another store Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 16 4

5 Advantages of Distributed Economics Many microprocessors that cooperatively work together offer better price/performance then a single large mainframe computer Speed A distributed system may have more total computing power then a mainframe Inherent Distribution Some applications involve spatially separated machines Reliability If one machine crashes, the system as a whole can still survive Incremental Growth Computing power can be added in small increments Advantages of Distributed over Isolated C s Data Sharing We desire to allow many users access a common data base Device Sharing Allow many users to share expensive peripherals like color laser printers Communication Make human-to-human communications easier (e.g., ) Flexibility Spread the workload over the available machines in the most cost effective ways The popularity of LAN, WAN, MAN and the Internet networks now makes distributed systems using standard C hardware possible Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 17 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 18 Disadvantages of Distributed Although distributed systems have many advantages, there are significant disadvantages Most are attributed to the relative youth of distributed system Software Little software exists at present for distributed systems The network can saturate or cause other problems Bandwidth forces design decisions Network reliability is an issue Security Managing security on a distributed system is complex New technologies such as Kerberous, LDA, ondemand and KI are now becoming commercially available Distributed System Hardware Distributed systems consist of multiple CU s There are many different ways that distributed systems can be organized Especially relevant on how the CU s are interconnected and how they communicate Classification SISD: Single CU, Single data stream. Examples: Traditional C s, Mainframes SIMD: Single CU, Multiple data stream Useful in systems that repeat the same calculation multiple times (e.g., matrix multiplication) Examples: Supercomputers, Vector processors MISD: Multiple CU s, Single data stream No known systems exist MIMD: Multiple CU s, Multiple data streams MIMD is widely utilized in distributed systems Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 19 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 20 5

6 MIMD Architectures MIMD Architectures come in several flavors Design alternatives Bus or Switched (Interconnectivity) Loosely or Tightly coupled (Bandwidth) Tightly Coupled MIMD arallel and Distributed Computers Loosely Coupled Tightly Coupled Multiprocessors Tightly coupled multiprocessors traditionally share a single memory among many CU s is connected to the CU s either using a bus or a switching fabric Shared Multiprocessors (Shared BUS Switched Multicomputers (rivate BUS Switched Interconnection Network (BUS or Switch) Cache 1 Cache Cache N N Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 21 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 22 Loosely Coupled Multicomputers Loosely Coupled Multicomputers Loosely coupled multicomputers traditionally network together a collection of CU s that each contain a private memory Interconnection between the CU s is accomplished by either a standard or proprietary (high-speed backplane) network May use a shared media(bus) or a switching mechanism (ATM) Loosely coupled multicomputers typically are connected with low bandwidth when compared to their tightly coupled counterparts ATM Switch Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 23 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 24 6

7 BUS-Based Interconnectivity Bus based distributed systems are typically useful with a relatively low number of CU s (< 64) Bus based interconnectivity may be accomplished by using: Standard LAN technology (10,16,100Mbit/Sec) Low speed dialup or leased line connectivity (33Kbit - T1) roprietary network (> 1Gbit/Sec) The bus is shared among all processors in the distributed system May lead to congestion because only one processor at a time can use the bus Need a mechanism to manage and allocate processors the bus Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 25 Switched Interconnectivity Switching technology is used to build large distributed systems Switching technology scales well because multiple processors can concurrently communicate over the communication channel Switching supports very high bandwidth Switch M M M M CROSSBAR Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 26 S S S S M M M M 2 X 2 SWITCH Distributed Software Network Operating Software is very critical to a distributed system The image that a system presents to its users and how they think about the system is largely determined by the operating system software Like hardware there are several classifications of distributed operating systems Network Operating Distributed Operating Multiprocessor Timesharing Operating Without a distributed operating system the user is responsible for managing the distributed environment Very complex, this is what an OS is suppose to handle Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 27 Operating system must manage individual workstations, file servers and the network connection between them File servers are used as to contain a repository of data that can be shared among the workstations connected to the network Each machine may run the same or different operating system Clients and servers must agree on the data exchange format (network protocol) Network operating systems are most commonly found in traditional LAN environments Windows NT Netware Unix Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 28 7

8 True Distributed The operating system provides the illusion that all of the distributed processors in the distributed environment act as a single timesharing system Virtual uni-processor Must be a single global interprocess communication mechanism Any process can talk to any other process, irregardless of where the processes are running Consistent process management policies are required Consistent file system image The file system must look the same everywhere even though individual files are based on different computers Multiprocessor Timesharing Single run queue that coordinates processes that are executing on distributed processes Good when central coordination is required Good when processes are highly compute bound Shared Interconnection Network (BUS or Switch) Cache 1 1 Cache 2 2 Centralized Run Queue... Cache N N Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 29 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 30 Comparing Distributed Operating Does it look like a virtual uniprocessor Do all processors run the same OS How many copies of the OS are there How is communication achieved Are agreed upon network protocols required How many run queues are there Does the sharing have well-defined semantics Network OS NO YES YES NO YES YES N N 1 Shared Files & Messages Messages Shared YES YES YES N N 1 Usually NO Distributed OS YES Multiprocessor OS YES Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 31 Caches Uniprocessor computers utilized cache memories to speedup execution The same holds true in distributed systems Although cache memory offers significant performance improvements, the use of caches in distributed systems can cause problems Must make sure that a consistent view of memory is provided to all processors in the system Need cache coherence protocols Bus snooping Directory based Single and distributed directories We will talk about cache coherence in detail later in the term Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 32 8

9 Design Issues for Distributed There are many design issues that are important when considering how to achieve a single system image in a distributed environment Transparency System designers fool users into thinking a collection of computers is a single timesharing system Flexibility System should be able to be logically configured in a flexible manner Reliability System should be able to tolerate one or more failures in the distributed environment Scalability System should scale well and limit the amount of central control Fundamental roperties of Distributed No machine has complete information about the global distributed systems state Individual machines make decisions based only on local information Failure of one machine does not ruin the algorithm There is no implicit assumption that a global clock exists Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 33 Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 34 References Distributed Operating, Andrew Tannenbaum, rentice Hall Advanced Computer Architecture - arallelism, Scalability & rogrammability, Kai Hwang, McGraw Hill Computer Architecture and Organization, Hayes, McGraw Hill Brian Mitchell (bmitchel@mcs.drexel.edu) - Distributed 35 9