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/*
* CONFIGURATION MACRO DEFINITIONS for sparse matrix routines
*
* Author: Advising professor:
* Kenneth S. Kundert Alberto Sangiovanni-Vincentelli
* U.C. Berkeley
*
* This file contains macros for the sparse matrix routines that are used
* to define the personality of the routines. The user is expected to
* modify this file to maximize the performance of the routines with
* his/her matrices.
*
* Macros are distinguished by using solely capital letters in their
* identifiers. This contrasts with C defined identifiers which are
* strictly lower case, and program variable and procedure names which use
* both upper and lower case.
*/
/*
* Revision and copyright information.
*
* Copyright (c) 1985,86,87,88,89,90
* by Kenneth S. Kundert and the University of California.
*
* Permission to use, copy, modify, and distribute this software and
* its documentation for any purpose and without fee is hereby granted,
* provided that the copyright notices appear in all copies and
* supporting documentation and that the authors and the University of
* California are properly credited. The authors and the University of
* California make no representations as to the suitability of this
* software for any purpose. It is provided `as is', without express
* or implied warranty.
*
* $Date$
* $Revision$
*/
#ifndef spCONFIG_DEFS
#define spCONFIG_DEFS
#ifdef spINSIDE_SPARSE
/*
* OPTIONS
*
* These are compiler options. Set each option to one to compile that
* section of the code. If a feature is not desired, set the macro
* to NO. Recommendations are given in brackets, [ignore them].
*
* >>> Option descriptions:
* Arithmetic Precision
* The precision of the arithmetic used by Sparse can be set by
* changing changing the spREAL macro. This macro is
* contained in the file spMatrix.h. It is strongly suggested to
* used double precision with circuit simulators. Note that
* because C always performs arithmetic operations in double
* precision, the only benefit to using single precision is that
* less storage is required. There is often a noticeable speed
* penalty when using single precision. Sparse internally refers
* to a spREAL as a RealNumber.
* EXPANDABLE
* Setting this compiler flag true (1) makes the matrix
* expandable before it has been factored. If the matrix is
* expandable, then if an element is added that would be
* considered out of bounds in the current matrix, the size of
* the matrix is increased to hold that element. As a result,
* the size of the matrix need not be known before the matrix is
* built. The matrix can be allocated with size zero and
* expanded.
* TRANSLATE
* This option allows the set of external row and column numbers
* to be non-packed. In other words, the row and column numbers
* do not have to be contiguous. The priced paid for this
* flexibility is that when TRANSLATE is set true, the time
* required to initially build the matrix will be greater because
* the external row and column number must be translated into
* internal equivalents. This translation brings about other
* benefits though. First, the spGetElement() and
* spGetAdmittance() routines may be used after the matrix has
* been factored. Further, elements, and even rows and columns,
* may be added to the matrix, and row and columns may be deleted
* from the matrix, after it has been factored. Note that when
* the set of row and column number is not a packed set, neither
* are the RHS and Solution vectors. Thus the size of these
* vectors must be at least as large as the external size, which
* is the value of the largest given row or column numbers.
* INITIALIZE
* Causes the spInitialize(), spGetInitInfo(), and
* spInstallInitInfo() routines to be compiled. These routines
* allow the user to store and read one pointer in each nonzero
* element in the matrix. spInitialize() then calls a user
* specified function for each structural nonzero in the matrix,
* and includes this pointer as well as the external row and
* column numbers as arguments. This allows the user to write
* custom matrix initialization routines.
* DIAGONAL_PIVOTING
* Many matrices, and in particular node- and modified-node
* admittance matrices, tend to be nearly symmetric and nearly
* diagonally dominant. For these matrices, it is a good idea to
* select pivots from the diagonal. With this option enabled,
* this is exactly what happens, though if no satisfactory pivot
* can be found on the diagonal, an off-diagonal pivot will be
* used. If this option is disabled, Sparse does not
* preferentially search the diagonal. Because of this, Sparse
* has a wider variety of pivot candidates available, and so
* presumably fewer fill-ins will be created. However, the
* initial pivot selection process will take considerably longer.
* If working with node admittance matrices, or other matrices
* with a strong diagonal, it is probably best to use
* DIAGONAL_PIVOTING for two reasons. First, accuracy will be
* better because pivots will be chosen from the large diagonal
* elements, thus reducing the chance of growth. Second, a near
* optimal ordering will be chosen quickly. If the class of
* matrices you are working with does not have a strong diagonal,
* do not use DIAGONAL_PIVOTING, but consider using a larger
* threshold. When DIAGONAL_PIVOTING is turned off, the following
* options and constants are not used: MODIFIED_MARKOWITZ,
* MAX_MARKOWITZ_TIES, and TIES_MULTIPLIER.
* MODIFIED_MARKOWITZ
* This specifies that the modified Markowitz method of pivot
* selection is to be used. The modified Markowitz method differs
* from standard Markowitz in two ways. First, under modified
* Markowitz, the search for a pivot can be terminated early if a
* adequate (in terms of sparsity) pivot candidate is found.
* Thus, when using modified Markowitz, the initial factorization
* can be faster, but at the expense of a suboptimal pivoting
* order that may slow subsequent factorizations. The second
* difference is in the way modified Markowitz breaks Markowitz
* ties. When two or more elements are pivot candidates and they
* all have the same Markowitz product, then the tie is broken by
* choosing the element that is best numerically. The numerically
* best element is the one with the largest ratio of its magnitude
* to the magnitude of the largest element in the same column,
* excluding itself. The modified Markowitz method results in
* marginally better accuracy. This option is most appropriate
* for use when working with very large matrices where the initial
* factor time represents an unacceptable burden. [NO]
* DELETE
* This specifies that the spDeleteRowAndCol() routine
* should be compiled. Note that for this routine to be
* compiled, both DELETE and TRANSLATE should be set true.
* STRIP
* This specifies that the spStripFills() routine should be compiled.
* MODIFIED_NODAL
* This specifies that the routine that preorders modified node
* admittance matrices should be compiled. This routine results
* in greater speed and accuracy if used with this type of
* matrix.
* QUAD_ELEMENT
* This specifies that the routines that allow four related
* elements to be entered into the matrix at once should be
* compiled. These elements are usually related to an
* admittance. The routines affected by QUAD_ELEMENT are the
* spGetAdmittance, spGetQuad and spGetOnes routines.
* TRANSPOSE
* This specifies that the routines that solve the matrix as if
* it was transposed should be compiled. These routines are
* useful when performing sensitivity analysis using the adjoint
* method.
* SCALING
* This specifies that the routine that performs scaling on the
* matrix should be complied. Scaling is not strongly
* supported. The routine to scale the matrix is provided, but
* no routines are provided to scale and descale the RHS and
* Solution vectors. It is suggested that if scaling is desired,
* it only be preformed when the pivot order is being chosen [in
* spOrderAndFactor()]. This is the only time scaling has
* an effect. The scaling may then either be removed from the
* solution by the user or the scaled factors may simply be
* thrown away. [NO]
* DOCUMENTATION
* This specifies that routines that are used to document the
* matrix, such as spPrint() and spFileMatrix(), should be
* compiled.
* DETERMINANT
* This specifies that the routine spDeterminant() should be complied.
* STABILITY
* This specifies that spLargestElement() and spRoundoff() should
* be compiled. These routines are used to check the stability (and
* hence the quality of the pivoting) of the factorization by
* computing a bound on the size of the element is the matrix E =
* A - LU. If this bound is very high after applying
* spOrderAndFactor(), then the pivot threshold should be raised.
* If the bound increases greatly after using spFactor(), then the
* matrix should probably be reordered.
* CONDITION
* This specifies that spCondition() and spNorm(), the code that
* computes a good estimate of the condition number of the matrix,
* should be compiled.
* PSEUDOCONDITION
* This specifies that spPseudoCondition(), the code that computes
* a crude and easily fooled indicator of ill-conditioning in the
* matrix, should be compiled.
* MULTIPLICATION
* This specifies that the routines to multiply the unfactored
* matrix by a vector should be compiled.
* DEBUG
* This specifies that additional error checking will be compiled.
* The type of error checked are those that are common when the
* matrix routines are first integrated into a user's program. Once
* the routines have been integrated in and are running smoothly, this
* option should be turned off.
*/
/* Begin options. */
#define EXPANDABLE YES
#define TRANSLATE YES
#define INITIALIZE NO
#define DIAGONAL_PIVOTING YES
#define MODIFIED_MARKOWITZ NO
#define DELETE NO
#define STRIP NO
#define MODIFIED_NODAL YES
#define QUAD_ELEMENT NO
#define TRANSPOSE YES
#define SCALING NO
#define DOCUMENTATION YES
#define MULTIPLICATION YES
#define DETERMINANT YES
#define DETERMINANT2 YES
#define STABILITY NO
#define CONDITION NO
#define PSEUDOCONDITION NO
#ifdef HAS_MINDATA
# define DEBUG NO
#else
# define DEBUG YES
#endif
/*
* The following options affect Sparse exports and so are exported as a
* side effect. For this reason they use the `sp' prefix. The boolean
* constants YES an NO are not defined in spMatrix.h to avoid conflicts
* with user code, so use 0 for NO and 1 for YES.
*/
/*
* MATRIX CONSTANTS
*
* These constants are used throughout the sparse matrix routines. They
* should be set to suit the type of matrix being solved. Recommendations
* are given in brackets.
*
* Some terminology should be defined. The Markowitz row count is the number
* of non-zero elements in a row excluding the one being considered as pivot.
* There is one Markowitz row count for every row. The Markowitz column
* is defined similarly for columns. The Markowitz product for an element
* is the product of its row and column counts. It is a measure of how much
* work would be required on the next step of the factorization if that
* element were chosen to be pivot. A small Markowitz product is desirable.
*
* >>> Constants descriptions:
* DEFAULT_THRESHOLD
* The relative threshold used if the user enters an invalid
* threshold. Also the threshold used by spFactor() when
* calling spOrderAndFactor(). The default threshold should
* not be less than or equal to zero nor larger than one. [0.001]
* DIAG_PIVOTING_AS_DEFAULT
* This indicates whether spOrderAndFactor() should use diagonal
* pivoting as default. This issue only arises when
* spOrderAndFactor() is called from spFactor().
* SPACE_FOR_ELEMENTS
* This number multiplied by the size of the matrix equals the number
* of elements for which memory is initially allocated in
* spCreate(). [6]
* SPACE_FOR_FILL_INS
* This number multiplied by the size of the matrix equals the number
* of elements for which memory is initially allocated and specifically
* reserved for fill-ins in spCreate(). [4]
* ELEMENTS_PER_ALLOCATION
* The number of matrix elements requested from the malloc utility on
* each call to it. Setting this value greater than 1 reduces the
* amount of overhead spent in this system call. On a virtual memory
* machine, its good to allocate slightly less than a page worth of
* elements at a time (or some multiple thereof).
* [For the VAX, for real only use 41, otherwise use 31]
* MINIMUM_ALLOCATED_SIZE
* The minimum allocated size of a matrix. Note that this does not
* limit the minimum size of a matrix. This just prevents having to
* resize a matrix many times if the matrix is expandable, large and
* allocated with an estimated size of zero. This number should not
* be less than one.
* EXPANSION_FACTOR
* The amount the allocated size of the matrix is increased when it
* is expanded.
* MAX_MARKOWITZ_TIES
* This number is used for two slightly different things, both of which
* relate to the search for the best pivot. First, it is the maximum
* number of elements that are Markowitz tied that will be sifted
* through when trying to find the one that is numerically the best.
* Second, it creates an upper bound on how large a Markowitz product
* can be before it eliminates the possibility of early termination
* of the pivot search. In other words, if the product of the smallest
* Markowitz product yet found and TIES_MULTIPLIER is greater than
* MAX_MARKOWITZ_TIES, then no early termination takes place.
* Set MAX_MARKOWITZ_TIES to some small value if no early termination of
* the pivot search is desired. An array of RealNumbers is allocated
* of size MAX_MARKOWITZ_TIES so it must be positive and shouldn't
* be too large. Active when MODIFIED_MARKOWITZ is 1 (true). [100]
* TIES_MULTIPLIER
* Specifies the number of Markowitz ties that are allowed to occur
* before the search for the pivot is terminated early. Set to some
* large value if no early termination of the pivot search is desired.
* This number is multiplied times the Markowitz product to determine
* how many ties are required for early termination. This means that
* more elements will be searched before early termination if a large
* number of fill-ins could be created by accepting what is currently
* considered the best choice for the pivot. Active when
* MODIFIED_MARKOWITZ is 1 (true). Setting this number to zero
* effectively eliminates all pivoting, which should be avoided.
* This number must be positive. TIES_MULTIPLIER is also used when
* diagonal pivoting breaks down. [5]
* DEFAULT_PARTITION
* Which partition mode is used by spPartition() as default.
* Possibilities include
* spDIRECT_PARTITION -- each row used direct addressing, best for
* a few relatively dense matrices.
* spINDIRECT_PARTITION -- each row used indirect addressing, best
* for a few very sparse matrices.
* spAUTO_PARTITION -- direct or indirect addressing is chosen on
* a row-by-row basis, carries a large overhead, but speeds up
* both dense and sparse matrices, best if there is a large
* number of matrices that can use the same ordering.
*/
/* Begin constants. */
#define DEFAULT_THRESHOLD 1.0e-3
#define DIAG_PIVOTING_AS_DEFAULT YES
#define SPACE_FOR_ELEMENTS 6
#define SPACE_FOR_FILL_INS 4
#define ELEMENTS_PER_ALLOCATION 31
#define MINIMUM_ALLOCATED_SIZE 6
#define EXPANSION_FACTOR 1.5
#define MAX_MARKOWITZ_TIES 100
#define TIES_MULTIPLIER 5
#define DEFAULT_PARTITION spAUTO_PARTITION
/*
* PRINTER WIDTH
*
* This macro characterize the printer for the spPrint() routine.
*
* >>> Macros:
* PRINTER_WIDTH
* The number of characters per page width. Set to 80 for terminal,
* 132 for line printer.
*/
/* Begin printer constants. */
#define PRINTER_WIDTH 80
/*
* MACHINE CONSTANTS
*
* These numbers must be updated when the program is ported to a new machine.
*/
/* Begin machine constants. */
/*
* Grab from Spice include files
*/
#include "ngspice.h"
#define MACHINE_RESOLUTION DBL_EPSILON
#define LARGEST_REAL DBL_MAX
#define SMALLEST_REAL DBL_MIN
#define LARGEST_SHORT_INTEGER SHRT_MAX
#define LARGEST_LONG_INTEGER LONG_MAX
/*
* ANNOTATION
*
* This macro changes the amount of annotation produced by the matrix
* routines. The annotation is used as a debugging aid. Change the number
* associated with ANNOTATE to change the amount of annotation produced by
* the program.
*/
/* Begin annotation definitions. */
#define ANNOTATE NONE
#define NONE 0
#define ON_STRANGE_BEHAVIOR 1
#define FULL 2
#endif /* spINSIDE_SPARSE */
#endif /* spCONFIG_DEFS */