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Memory Operations in Scalable Massive Parallel Systems

IP.com Disclosure Number: IPCOM000106855D
Original Publication Date: 1993-Dec-01
Included in the Prior Art Database: 2005-Mar-21
Document File: 2 page(s) / 45K

Publishing Venue

IBM

Related People

Pomerene, J: AUTHOR [+2]

Abstract

The ability to share memory through a common memory map in a scalable massively parallel system can exploit the structure of DATA PARALLELISM and coordinate data set/use without SEND/RECEIVE and without software locks.

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Memory Operations in Scalable Massive Parallel Systems

      The ability to share memory through a common memory map in a
scalable massively parallel system can exploit the structure of DATA
PARALLELISM and coordinate data set/use without SEND/RECEIVE and
without software locks.

      DEFINITION OF DATA PARALLELISM - Consider a datum which is
represented by &doubleP.  and an algorithm &doubleZ.  so that the
result &doubleQ.  is achieved by:

               &doubleZ.:&doubleP.  &determines.  &doubleQ.

      Now we consider a partition of &doubleP.  represented by

           &doubleP.  = { <P sub 1> &cplus.  <P sub 2> &cplus.  <P
sub 3> &cplus.  ...  <&cplus.> <P sub n> }

      and a partition of &doubleQ.  represented by

           &doubleQ.  = { <Q sub 1> &cplus.  <Q sub 2> &cplus.  <Q
sub 3> &cplus.  ...  <&cplus.> <Q sub n> }

      Let us define a new algorithm <&doubleC.> sub i such that:

               <&doubleC.>sub i

       sub i &determines.  Q sub i for all i=1,2, ....  , n
and execute the n copies of <&doubleC.> sub i in parallel.  This form
of parallelism is called DATA PARALLELISM.

      Assume that each of the programs <&doubleC.> sub i is a single
assignment program.  Thus, each of the datum that is owned by
<&doubleC.> sub i, namely <&doubleQ.> sub i is set precisely once and
no other instruction executing on any other processor in the network
can change its...