Ioana BurceaWon-Ho Park

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Algorithms for Implementation of Tuple
SpaceExpert TopicECE 1770 Spring 2003

• Ioana Burcea Won-Ho Park
• Electrical and Computer Engineering Department
• University of Toronto

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Agenda

• Ioana
• Matching Algorithms (in Linda)
• Basic Terminology and Concepts
• Multi-Key Search Algorithm
• Won-Ho
• Linda Implementation of Tuple Space

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Basic Terminology

• Tuple (out operation)
• Ex
• (1, 4.0, Middleware)
• Template antituple (in operation)
• Ex
• (1, 4.0, ?x) x string
• (1, 4.0, Middleware)
• Tuple arity
• Ex
• (1, ?x) ? arity 2
• (1, 4.0, Middleware) ? arity 3
• Type signature
• Ex
• (1, 4.0, Middleware) ? (int, float, string)

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Matching Algorithms

• Exhaustive search too time consuming
• Optimizations
• Segmenting
• Orthogonal subspaces
• Based on
• tuple arity type signature
• constants
• Treated separately
• Searching
• Zero variable case
• In(mutex) Out(mutex)
• One variable case
• Single key index
• Multiple variable
• Multiple key search

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Patterns

• Actual parameter
• Ex
• (1, 4.0, Middleware) ? 1, 4.0, Middleware
• (1, 4.0, x) ? 1, 4.0, x
• Formal parameter (placeholder / wildcard)
• Ex
• ?x (x string)
• Tuple Pattern
• Bitvector
• its size is given by the arity of the tuple
• a bit is set if and only if it corresponds to a
  actual parameter
• Ex
• (1, 4.0, Middleware) ? (111)
• (1, 4.0. ?x) ? (110)

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Matching Semantics Using Patterns

• Compatible patterns
• Two tuples P and Q are compatible if and only if
  P OR Q contains only 1s
• Two tuples may match if and only if their
  patterns are compatible
• Must-match pattern
• Ex
• Out(a, b, c) ? pattern (111)
• In (x, ?y, z) ? pattern (101)
• Matching definition
• Two tuples match if and only if
• They have the same type signature
• Exactly one is an antituple
• Their patterns are compatible
• Their must-match values are equal

OR (111) ? compatible
AND (101) ? must-match pattern
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Multiple key search

• Applied inside each orthogonal subspace
• Basic idea
• Build the key search based on the pairs of
  compatible patterns and must-match values
• Ex
• Tuple pattern (111)
• Antituple patterns (010), (100), (110)
• an entry in the dictionary for each pair (tupple
  pattern, antituple pattern) gt each tuple will be
  referenced by multiple keys
• the key of the entry also contains the must-match
  values
• the entry points to the tuple
• Ex out(3, 5, x) gt Key (0101115)
• ! One record per must-match pattern is not
  sufficient !
• Property
• If two tuples have the same key gt they match

• Perfect hash function one to one correspondence
  between search keys and the hash keys

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Offline Algorithm in operation
1) Lock subspace 2) Identify antituples pattern,
p, and store antituple where it can be found
via a pointer or other reference. 3) For each
compatible tuple pattern, c, in use, 4)
Combine p, c, and antituples must-match values
to form a search key, k. 5)
Search dictionary for a tuple reference indexed
by k. 6) If one is found, then 7)
Delete tuple, antituple and all their
references. 8) Goto 10.
else 9) Insert a reference to
antituple, indexed by k,
into dictionary. 10) Unlock subspace 11) If no
match was found, then 12) Suspend
execution until signalled else 13)
Return match result
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Online Algorithm

• Adapt the tuple space whenever a new pattern is
  encountered

2.1) If p is a new antituple pattern, then 2.2)
Create a new list for p 2.3) For each
old, compatible tuple pattern q 2.4)
For each tuple t on qs list 2.5)
Insert into dictionary a new reference to t,
based on p and q 2.6)
Insert antituple in ps list

• Discussion
• Usually, no perfect hash
• Each hash entry has a hash chain
• The hash chain has to be checked until a match is
  found

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Virtual Linda Machine (VLM)Implementation of
Linda on Networks

• TupleSpaces is a virtually shared memory
• How to implement TupleSpaces in the absence of
  shared memory
• How to find Tuples and where keep them
• Components of VLM
• Hardware
• Network Communication Kernel
• Compiler
• Hardware is networks, or network computers
• The kernel is the program resident on each
  network node that implements inter-node
  communication
• Performing In(), out(), read() primitive
  instructions on networks by sending or
  broadcasting messages
• The compiler adds code for maintaining buffer
  (shared memory)

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Run-Time Name Resolution in VLMHow to find
Tuples

• VLM should provide Name(Tuple)-to-Node(address)
  mapping information
• Centralized in directory nodes
• Distributed network-wide (e.g., by means of a
  network-wide broadcast)
• The communication kernel translates Tuple-names
  into network-addresses on a per-reference basis
• Network state and its storage
• Only one node generating state information
  maintains the state
• All nodes maintain all state by broadcasting
• VLM uses N1/2-Node Broadcast Technique.

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N1/2-Node Broadcast Techniqueand Name Resolution

• Write set row nodes
• Read set column nodes
• P-in-thread process
• P-out-thread process
• P-in-thread is intercepted by a P-out-thread on
  node k.
• A notification message is generated on k-node,
  and sent to m-node
• The message instructs m-node to send tuple(P) to
  n-node.

A Network Topology
P-out-thread
m
Out(P)
P-in-thread
k
n
In(P)
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BufferingWhere to keep Tuples

• VLM is required to simulate Lindas infinite
  global buffer
• Buffer is allocated by the compiler-generated
  code, not by the kernel
• in(P.) allocating a buffer on the execution
  stack of the process, and referred to buffer P.
• out(P) Tuples are stored in per-process heaps,
  and destroyed when it is delivered
• Header information required by the communication
  system
• If a process terminates with undelivered Tuples
• The buffers are maintained by the communication
  kernel until delivery occurs