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version 1.4, 2001/06/20 02:50:16 version 1.6, 2001/06/20 03:18:21
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 % $OpenXM: OpenXM/doc/ascm2001p/homogeneous-network.tex,v 1.3 2001/06/20 02:39:25 noro Exp $  % $OpenXM: OpenXM/doc/ascm2001p/homogeneous-network.tex,v 1.5 2001/06/20 03:08:05 takayama Exp $
   
 \subsection{Distributed computation with homogeneous servers}  \subsection{Distributed computation with homogeneous servers}
 \label{section:homog}  \label{section:homog}
   
 One of the aims of OpenXM is a parallel speedup by a distributed computation  One of the aims of OpenXM is a parallel speedup by a distributed computation
 with homogeneous servers. As the current specification of OpenXM does  with homogeneous servers.
 not include communication between servers, one cannot expect  %As the current specification of OpenXM does
 the maximal parallel speedup. However it is possible to execute  %not include communication between servers, one cannot expect
 several types of distributed computation as follows.  %the maximal parallel speedup. However it is possible to execute
   %several types of distributed computation as follows.
   
 \subsubsection{Competitive distributed computation by various strategies}  \subsubsection{Competitive distributed computation by various strategies}
   
 SINGULAR \cite{Singular} implements {\it MP} interface for distributed  SINGULAR \cite{Singular} implements {\it MP} interface for distributed
 computation and a competitive Gr\"obner basis computation is  computation and a competitive Gr\"obner basis computation is
 illustrated as an example of distributed computation.  illustrated as an example of distributed computation.
 Such a distributed computation is also possible on OpenXM as follows:  Such a distributed computation is also possible on OpenXM.
   
 The client creates two servers and it requests  
 Gr\"obner basis comutations by the Buchberger algorithm the $F_4$ algorithm  
 to the servers for the same input.  
 The client watches the streams by {\tt ox\_select()}  
 and the result which is returned first is taken. Then the remaining  
 server is reset.  
   
 \begin{verbatim}  \begin{verbatim}
 extern Proc1,Proc2$  extern Proc1,Proc2$ Proc1 = -1$ Proc2 = -1$
 Proc1 = -1$ Proc2 = -1$  
 /* G:set of polys; V:list of variables */  /* G:set of polys; V:list of variables */
 /* Mod: the Ground field GF(Mod); O:type of order */  /* Mod: the Ground field GF(Mod); O:type of order */
 def dgr(G,V,Mod,O)  def dgr(G,V,Mod,O)
Line 49  def dgr(G,V,Mod,O)
Line 42  def dgr(G,V,Mod,O)
   return [Win,R];    return [Win,R];
 }  }
 \end{verbatim}  \end{verbatim}
   In the above Asir program, the client creates two servers and it requests
   Gr\"obner basis comutations by the Buchberger algorithm the $F_4$ algorithm
   to the servers for the same input.
   The client watches the streams by {\tt ox\_select()}
   and the result which is returned first is taken. Then the remaining
   server is reset.
   
 \subsubsection{Nesting of client-server communication}  \subsubsection{Nesting of client-server communication}
   
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