forked from xiaoyeli/superlu_mt
-
Notifications
You must be signed in to change notification settings - Fork 0
/
README
145 lines (113 loc) · 6.33 KB
/
README
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
SuperLU_MT (version 4.0.0)
==========================
SuperLU_MT contains a set of subroutines to solve a sparse linear system
A*X=B. It uses Gaussian elimination with partial pivoting (GEPP).
The columns of A may be preordered before factorization; the
preordering for sparsity is completely separate from the factorization.
SuperLU_MT is a parallel extension to the serial SuperLU library.
SuperLU_MT is implemented in ANSI C, with multithreading extension,
for example, using POSIX threads or OpenMP. Currently, only the LU
factorization routine, which is the most time-consuming part of the
solution process, is parallelized on machines with a shared address space.
The other routines, such as column preordering and the forward and
back substitutions are performed sequentially.
The library provides functionality for both real and complex
matrices, in both single and double precision.
The distribution contains the following directory structure:
superlu_mt/README instructions on installation
superlu_mt/CBLAS/ BLAS routines in C, functional but not fast
superlu_mt/DOC/ Users' Guide
superlu_mt/EXAMPLE/ example programs
superlu_mt/INSTALL/ test machine dependent parameters; the Users' Guide.
superlu_mt/MAKE_INC/ sample machine-specific make.inc files
superlu_mt/SRC/ C source code, to be compiled into libsuperlu_mt.a
superlu_mt/TESTING/ driver routines to test correctness
superlu_mt/lib/ SuperLU_MT library archive libsuperlu_mt.a
superlu_mt/Makefile top level Makefile that does installation and testing
superlu_mt/make.inc compiler, compile flags, library definitions and C
preprocessor definitions, included in all Makefiles.
(You may need to edit it to suit your system
before compiling the whole package.)
Before installing the package, please examine the three things dependent
on your system setup:
1. Edit the make.inc include file.
This make include file is referenced inside each of the Makefiles
in the various subdirectories. As a result, there is no need to
edit the Makefiles in the subdirectories. All information that is
machine specific has been defined in this include file.
The following machine-specific make.inc files are provided in the
MAKE_INC/ directory:
make.inc CPP in CFLAGS Platforms
-------- ------------- ---------
make.pthread -D__PTHREAD POSIX threads
make.openmp -D__OPENMP OpenMP
make.xe6 OpenMP or POSIX threads
make.cray -D__CRAY Cray C90/J90
make.ibm -D__PTHREAD IBM Power series
make.origin -D__ORIGIN SGI/Cray Origin2000
make.sun -D__SOLARIS Sun Ultra Enterprise servers
In each case, the CFLAGS should include a CPP definition to choose the
proper thread program interface. For example, in make.pthread, need:
CFLAGS = -D__PTHREAD ...
When you have selected the machine to which you wish to install SuperLU_MT,
copy the appropriate sample include file (if one is present) into
make.inc. For example, if you wish to run SuperLU_MT on a XE6 system,
you can do
cp MAKE_INC/make.xe6 make.inc
For the systems other than listed above, some porting effort is needed
for parallel factorization routines. Please refer to the Users' Guide
for detailed instructions on porting.
The other CPP definitions can be set in CFLAGS as follows:
o -D_LONGINT
use 64-bit integers for indexing sparse matrices. (default is 32-bit)
o -DPRNTlevel=[0,1,2,...]
printing level to show solver's execution details. (default is 0)
o -DDEBUGlevel=[0,1,2,...]
diagnostic printing level for debugging purpose. (default is 0)
2. The BLAS library.
*********************************************************
** NOTE: must link with a single-thread BLAS library. *
*********************************************************
The parallel routines in SuperLU_MT uses some sequential BLAS routines
within each process (or thread). If there is BLAS library available on
your machine, you may define the following in the file make.inc:
BLASDEF = -DUSE_VENDOR_BLAS
BLASLIB = <BLAS library you wish to link with>
The CBLAS/ subdirectory contains the part of the C BLAS needed by
SuperLU_MT package. However, these codes are intended for use only if
there is no faster implementation of the BLAS already available on your
machine. In this case, you should go to the top-level SuperLU_MT/
directory and do the following:
1) In make.inc, undefine (comment out) BLASDEF, and define:
BLASLIB = ../lib/libblas$(PLAT).a
2) Type:
make blaslib
to make the BLAS library from the routines in the CBLAS/ subdirectory.
3. C preprocessor definition CDEFS.
In the header file SRC/Cnames.h, we use macros to determine how
C routines should be named so that they are callable by Fortran.
(Some vendor-supplied BLAS libraries do not have C interface. So the
re-naming is needed in order for the SuperLU BLAS calls (in C) to
interface with the Fortran-style BLAS.)
The possible options for CDEFS are:
o -DAdd_: Fortran expects a C routine to have an underscore
postfixed to the name;
o -DNoChange: Fortran expects a C routine name to be identical to
that compiled by C;
o -DUpCase: Fortran expects a C routine name to be all uppercase.
A Makefile is provided in each subdirectory. The installation can be done
completely automatically by simply typing "make" at the top level.
REFERENCES
[1] A Supernodal Approach to Sparse Partial Pivoting,
James W. Demmel, Stanley C. Eisenstat, John R. Gilbert, Xiaoye S. Li
and Joseph W.H. Liu,
SIAM J. on Matrix Anal. and Appl., vol 20(3), 720-755, 1999.
[2] An Asynchronous Parallel Supernodal Algorithm for Sparse Gaussian
Elimination, James W. Demmel, John R. Gilbert and Xiaoye S. Li,
SIAM J. Matrix Anal. Appl., vol. 20(4), 915-952, 1999.
[3] Sparse Gaussian Elimination on High Performance Computers,
Xiaoye S. Li, Tech report UCB//CSD-96-919, Computer Science Division,
U.C. Berkeley, September, 1996, Ph.D dissertation.
Xiaoye S. Li, Lawrence Berkeley National Lab, [email protected]
James Demmel, UC Berkeley, [email protected]
John R. Gilbert, UC Santa Barbara, [email protected]