GENERATIVE COMMUNICATION IN LINDA AND OBJECT/TUPLE SPACE - Sheng Tian, shengt@gmail.com

LINDA: COORDINATION AMONG PARALLEL PROCESSES THROUGH TUPLE SPACE.

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COMMUNICATE VIA TUPLE SPACE

To send to B, A generates a tuple out(N, P2, …, Pj)

… and B withdraws it in(N, P2, …, Pj) 3

BASIC OPERATIONS ON THE TUPLES AND TUPLE SPACES   Tuple: N, P2, …, Pj

  N is an actual parameter of type name   P2, …, Pj is a list of parameters each of which may be either an actual or a

formal.

  Insert: out(N, P2, …, Pj)   Execution of the out() statement results in insertion of the tuple N, P2,

…, Pj into TS   Blocking read and delete: in(N, P2, …, Pj)

  If some type-consonant tuple whose first component is “N” exists in TS, the tuple withdraw from TS

  If no matching tuple is available in TS, in() suspends until one is available

  Blocking read: read(N, P2, …, Pj)   Same as in() statement but the tuple remains in TS.   Both in() and read() are logically nondeterminism

  Tuple names are global to a given program’s TS.   Update tuple: delete and reinsert   Predicate operations: inp and rdp 4

TUPLE SPACES BASICS OPERATIONS

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AGENDA

 Background  Basic Concepts in Generative Communication  Distinguishing Properties of Linda  Case Study  Discussion

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BACKGROUND

 Three basic models of concurrent programming:   Monitors (shared variables)   Message passing   Remote Operations

 Cons   Partially distributed in space   Nondistributed in time

 New Model: Generative communication   Fully distributed in space and time

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BASIC CONCEPTS   Tuple

  A tuple is a fixed-length list containing elements that do not need to have the same type.

  Tuple/Object Space   A virtual repository of tuple, shared amongst providers and accessors

of network services, that can be accessed concurrently   All the participants of the distributed application share an Object

Space.   Processes communicate among each other using these shared objects –

by updating the state of the objects as and when needed

  Linda   A model of coordination and communication among several parallel

processes operating upon objects stored in and retrieved from Tuple Space.

  Generative Communication Model   Why it is said to be generative? Because, until it is explicitly

withdrawn, the tuple generated by A has an independent existence in TS.

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DISTINGUISHING PROPERTIES (1/2)

 Communication orthogonality   p1: Space-uncoupling

  A tuple in TS tagged “P” may be input by any number of address-space-disjoint processes

  p2: Time-uncoupling   Tuples added to TS by out() remains in TS until it is

removed by in()

  p3: Distributed sharing   Linda allows j address-space-disjoint processes to share

some variable v by depositing it in TS.

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SPACE AND TIME UNCOUPLING

Space-disjoint processes A and B communicate via TS

Time-disjoint processes C and D. C terminates before D starts – Likewise communicate via TS 10

DISTINGUISHING PROPERTIES (2/2)

  Free naming   p4: Support for continuation passing

  Linda allows name-type values to be tuple components and to be stored in arbitrary data structures in the same way as values of any other type.

  p5: Structured naming   Structured naming make TS content-addressable   e.g.

  The statement   in(P, i: integer, j:boolean)

  Requests a tuple with name “P”, but it is also possible to write   in(P, i:integer, FALSE) and in(P, 2, FALSE)

  It allows in() and read() statements to restrict, and out() statements to widen, their focus.

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CASE STUDY (1/2)

  Database Search Problem   We are given a file containing a set of search data, a target,

and a routine that computes a numeric score for single datum/target pair.

  A manager makes a series of out requests to place the search data in the tuple space, then performs in operations to retrieve the results generated by workers

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CASE STUDY (2/2)

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begin count = 0 until EOF do read datum from file OUT("datum", datum) count = count + 1 enddo best = 0.0 for i = 1 to count IN("score", value) if value > best then best = value

endfor for i = 1 to numworkers OUT("datum", "stop") endfor

end

begin IN("datum", datum) until datum = "stop" do

value = compare(datum, target)

OUT("score", value)

IN("datum", datum)

enddo end

procedure manager procedure worker

SPACE BASED ARCHITECTURE

  Object Spaces is a paradigm for development of distributed computing applications.

  Spaces can be used to achieve scalability through parallel procesing.

  Objects, when deposited in an Object Space are passive, i.e., their methods cannot be invoked while the objects are in the Object Space.

  This paradigm inherently provides mutual exclusion.   Linda coordination language was developed at Yale.   Object Spaces is usually called Tuple Spaces since it

contains of tuples unrelated to each others. 14

IMPLEMENTATIONS OF TUPLE SPACES   Java

  Sun’s JavaSpaces   GigaSpaces   OpenSpaces

  IBM’s Tspaces   ActiveSpace   Jada   LighTS   Jxtaspaces for P2P   GLOBE   Blitz

  C   Scientific Computing

Associates’ TCP-Linda   W.F. Wong’s Simple C-

Linda with Posix Threads

  HTML Page Spaces   Masatoshi Seki’s Rinda,

part of DistributedRuby dRuby

  Ruple for Ruby   p4-Linda   Python

  PyBrenda in Python   PyLinda. Linda

implementation in Python   Matlab: NetWorkSpaces

  Note:   Ruple use XML documents

instead of tuples 15

DISCUSSION (1/2)

  Message queue vs. Tuple space   Messages go from one person to another. Only the intended

recipient of a message gets to see it.   Tuple Space is a bag with tuple in it. The tuples in TS can

be read and processed by anyone.   It is possible to force sequencing of messages by including a

time, matching on all messages, then selecting the message with the earliest time.

  Message passing must has a destination. No matter it's a single dest or a group. However Tuple space is distributed. Workers don't know each other.

  Broadcast messages are not like Tuple Space.   A broadcast message is received by everyone whether they

want it or not   Tuples are extracted or copied under the control of the reader/

receiver 16

DISCUSSION (2/2)

 Tuple Space Scalability   Tuple Space won’t work on the Internet, because of

its underlying “distributed shared memory” idea

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