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psblas3:
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@@ -77,7 +77,7 @@ The serial parts of the computation on each process are executed through
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calls to the serial sparse BLAS subroutines. In a similar way, the
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inter-process message exchanges are implemented through the Basic
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Linear Algebra Communication Subroutines (BLACS) library [<A
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HREF="node108.html#BLACS">6</A>]
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HREF="node108.html#BLACS">7</A>]
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that guarantees a portable and efficient communication layer. The
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Message Passing Interface code is encapsulated within the BLACS
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layer. However, in some cases, MPI routines are directly used either
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@@ -90,7 +90,7 @@ user does not need to delve into their details (see Sec. <A HREF="node73.ht
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<P>
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<DIV ALIGN="CENTER"><A NAME="fig:psblas"></A><A NAME="224"></A>
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<DIV ALIGN="CENTER"><A NAME="fig:psblas"></A><A NAME="226"></A>
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<TABLE>
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<CAPTION ALIGN="BOTTOM"><STRONG>Figure 1:</STRONG>
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PSBLAS library components hierarchy.</CAPTION>
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@@ -141,7 +141,7 @@ as well as completely arbitrary assignments of
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equation indices to processes. In particular it is consistent with the
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usage of graph partitioning tools commonly available in the
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literature, e.g. METIS [<A
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HREF="node108.html#METIS">11</A>].
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HREF="node108.html#METIS">13</A>].
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Dense vectors conform to sparse
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matrices, that is, the entries of a vector follow the same distribution
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of the matrix rows.
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@@ -152,7 +152,7 @@ process generates its own portion. We never require that the entire
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matrix be available on a single node. However, it is possible
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to hold the entire matrix in one process and distribute it
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explicitly<A NAME="tex2html2"
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HREF="footnode.html#foot165"><SUP>1</SUP></A>, even though the resulting
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HREF="footnode.html#foot167"><SUP>1</SUP></A>, even though the resulting
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bottleneck would make this option unattractive in most cases.
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<P>
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