Chapter1 - Chapter 1: Introduction Ajay Kshemkalyani and...

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Chapter 1: Introduction Ajay Kshemkalyani and Mukesh Singhal Distributed Computing: Principles, Algorithms, and Systems Cambridge University Press Introduction CUP 2008 1 / 36
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Distributed Computing: Principles, Algorithms, and Systems Definition Autonomous processors communicating over a communication network Some characteristics I No common physical clock I No shared memory I Geographical seperation I Autonomy and heterogeneity Introduction CUP 2008 2 / 36
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Distributed Computing: Principles, Algorithms, and Systems Distributed System Model M memory bank(s) P P P P P P P M M M M M M M Communication network (WAN/ LAN) P processor(s) Figure 1.1: A distributed system connects processors by a communication network. Introduction CUP 2008 3 / 36
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Distributed Computing: Principles, Algorithms, and Systems Relation between Software Components protocols Operating system Distributed software Network protocol stack Transport layer Data link layer Application layer (middleware libraries) Network layer Distributed application Extent of distributed Figure 1.2: Interaction of the software components at each process. Introduction CUP 2008 4 / 36
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Distributed Computing: Principles, Algorithms, and Systems Motivation for Distributed System Inherently distributed computation Resource sharing Access to remote resources Increased performance/cost ratio Reliability I availability, integrity, fault-tolerance Scalability Modularity and incremental expandability Introduction CUP 2008 5 / 36
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Distributed Computing: Principles, Algorithms, and Systems Parallel Systems Multiprocessor systems (direct access to shared memory, UMA model) I Interconnection network - bus, multi-stage sweitch I E.g., Omega, Butterfly, Clos, Shuffle-exchange networks I Interconnection generation function, routing function Multicomputer parallel systems (no direct access to shared memory, NUMA model) I bus, ring, mesh (w w/o wraparound), hypercube topologies I E.g., NYU Ultracomputer, CM* Conneciton Machine, IBM Blue gene Array processors (colocated, tightly coupled, common system clock) I Niche market, e.g., DSP applications Introduction CUP 2008 6 / 36
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Distributed Computing: Principles, Algorithms, and Systems UMA vs. NUMA Models M memory M P P P P P P M M M M M M M M M P P P P Interconnection network Interconnection network (a) (b) P processor Figure 1.3: Two standard architectures for parallel systems. (a) Uniform memory access (UMA) multiprocessor system. (b) Non-uniform memory access (NUMA) multiprocessor. In both architectures, the processors may locally cache data from memory. Introduction CUP 2008 7 / 36
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Distributed Computing: Principles, Algorithms, and Systems Omega, Butterfly Interconnects 3-stage Butterfly network 101 110 111 100 111 110 100 011 010 000 001 P0 P1 P2 P3 P4 P6 P7 101 P5 000 001 M0 M1 010 011 100 101 110 111 M2 M3 M4 M5 M6 M7 000 001 010 011 M0 M1 M2 M3 M4 M5 M6 M7 110 111 011 010 000 001 100 101 P0 P1 P2 P3 P4 P5 P6 P7 (a) 3-stage Omega network (n=8, M=4) (b) (n=8, M=4) Figure 1.4: Interconnection networks for shared memory multiprocessor systems.
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This note was uploaded on 02/23/2012 for the course COMP 553 taught by Professor Ajay during the Spring '12 term at Ill. Chicago.

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Chapter1 - Chapter 1: Introduction Ajay Kshemkalyani and...

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