Introduction Radu Nicolescu Department of Computer Science - PowerPoint PPT Presentation

Organisation Topics Basics Echo Further Readings Project Introduction Radu Nicolescu Department of Computer Science University of Auckland 16 July 2018 1 / 35

Organisation Topics Basics Echo Further Readings Project 1 Organisation 2 Distributed algorithms 3 Basics 4 Echo algorithm 5 Further algorithms 6 Readings 7 Project and practical work 2 / 35

Organisation Topics Basics Echo Further Readings Project Outline 1 Organisation 2 Distributed algorithms 3 Basics 4 Echo algorithm 5 Further algorithms 6 Readings 7 Project and practical work 3 / 35

Organisation Topics Basics Echo Further Readings Project Organisation • Before the break: weeks 1–4; after the break: weeks 11–12 • Contents: an introduction to a few fundamental distributed algorithms • Exam: theory of the distributed algorithms • Two projects: practical implementations (emulations of specific distributed algorithms on a single computer) 4 / 35

Organisation Topics Basics Echo Further Readings Project Distributed algorithms • Computing: computer systems, networking, computer architectures, computer programming, algorithms • Parallel computing: multi-processors/cores, parallel systems, threading, concurrency, data sharing and races, parallel programming (data and task parallelism), parallel algorithms • Distributed computing: distributed systems, message passing, communication channels, distributed architectures, distributed programming, distributed algorithms • concurrency of components • paramount messaging time • lack of global clock in the async case • independent failure of components • read more: http://en.wikipedia.org/w/index.php? title=Distributed_computing&oldid=616081922 6 / 35

Organisation Topics Basics Echo Further Readings Project Overlap between parallel and distributed computing • One litmus test: • Parallel computing: tight coupling between tasks • Distributed computing: loose coupling between nodes • Another difference – specific for algorithms: • In classical algorithms, the problem is encoded and given to the (one single) processing element • In parallel algorithms, the problem is encoded and partitioned, and then its chunks are given to the processing elements • In distributed algorithms, the problem is given by the network itself and solved by coordination protocols • read more: http://en.wikipedia.org/w/index.php? title=Distributed_algorithm&oldid=594511669 7 / 35

Organisation Topics Basics Echo Further Readings Project Typical scenario in distributed computing • computing nodes have local memories and unique IDs • nodes are arranged in a network: graph, digraph, ring, ... • neighbouring nodes can communicate by message passing • independent failures are possible: nodes, communication channels • the network topology (size, diameter, neighbourhoods) and other characteristics (e.g. latencies) are often unknown to individual nodes • the network may or may not dynamically change • nodes solve parts of a bigger problem or have individual problems but still need some sort of coordination – which is achieved by distributed algorithms 8 / 35

Organisation Topics Basics Echo Further Readings Project Recall from graph theory • Graphs, edges, digraphs, arcs, degrees, connected, complete graphs, size, distance, diameter, radius, paths, weights/costs, shortest paths, spanning trees, ... • distance between a pair of nodes = minimum length of a connecting path, aka length of a shortest path (hop count in unweighted graphs) • min • diameter = maximum distance, between any pair of nodes • max min • radius = minimum maximum distance, over all nodes (minimum attained at centers) • min max min 10 / 35

Introduction Radu Nicolescu Department of Computer Science - PowerPoint PPT Presentation

Organisation Topics Basics Echo Further Readings Project Introduction Radu Nicolescu Department of Computer Science University of Auckland 16 July 2018 1 / 35 Organisation Topics Basics Echo Further Readings Project 1 Organisation

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