Recent enhancements in MUDPACK , a multigrid software package for elliptic partial differential equations

Recent enhancements in MUDPACK , a multigrid software package for elliptic partial differential equations

Recent Enhancements in MUDPACK, a Multigrid Software Package for Elliptic Partial Differential Equations John C. Adams Nutional Center for Atmospher...

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Recent Enhancements in MUDPACK, a Multigrid Software Package for Elliptic Partial Differential Equations John

C. Adams

Nutional Center for Atmospheric P.O. Box 3000 Boulder, Colorado 80307

Research*

ABSTRACT

Enhancements discussed

1.

and

in a new illustrated

with

version

of the

multigrid

software

package

\IUIII’M:L

are

examples.

INTRODUCTION

The multigrid software package MUDPACK has undergone substantial revision since an earlier version dcscrihed in detail in this journal (see [I]). The changes include the availability of multigrid order solvers, the removal of some constraints

options, the addition of fourthon grid size, and the addition

of hybrid multigrid-direct-method solvers. These constitute a significant enhancement of the original package. The new version replaces and is incompatible with the earlier version. However, most of the details of the discretization, boundary conditions, relaxation methods, etc., contained in [l] are still accurate and are not repeated here. In the next section we briefly review the purpose and contents of MUDPACK. In the last two sections, we discuss each of the major changes and present examples which illustrate the advantages they provide. More atten-

*The National tion.

Center

for Atmospheric

Research

is sponsored

APPLZED MATHEMATZCS AND COMPCJTATZON 43:79-93 0 Elsevier Science Publishing Co., Inc., 1991 655 Avenue of the Americas, New York, NY 10010

by the National

Scienw

Founda-

(1991)

79

0096-3003/91/$03.50

JOHN C. ADAMS

80

tion is paid to supercomputer performance than in the examples given in [l, 21. Applications of the software to “real” problems taken from a variety of disciplines within the atmospheric sciences are given in [5].

2.

PACKAGE MUDPACK

tial equations

DESCRIPTION

software provides efficient solutions to elliptic partial differen(PDEs) using multigrid iteration [7, 8, 10, 121. The package is

user-friendly, is FORTRAN-77-portable, and vectorizes on Cray computers. The codes have been successfully run on a variety of computers and operating systems. Currently there are 27 FORTRAN solvers in the package for generating second- and fourth-order approximations to elliptic PDEs in a variety of forms. These include two- and three-dimensional, real and complex, separable and nonseparable, and self-adjoint equations. The solution regions are rectangular in the sense that the domain of each independent variable must be a bounded interval on the real line. This means that curvilinear coordinate systems such as spherical or cylindrical coordinates are acceptable. The codes are not restricted to Cartesian coordinates. Allowable boundary conditions include any combination of periodic, Dirichlet, or mixed derivative. The continuous problems are automatically discretized using second-order finite-difference formulae on uniform grids superimposed on the solution regions. This is transparent to a user, who only needs to supply the PDE, boundary conditions, and grid size. The discretization includes adjustment of second-order coefficients at coarser grid levels if there are nonzero first-order terms in the PDE which dominate and make it appear hyperbolic. If untreated, these can inhibit convergence. The resulting linear block-tridiagonal systems using multigrid iteration. Vectorized Gauss-Seidel

are approximately solved relaxation schemes based

on alternating points (red-black), lines, or planes (for three-dimensional anisotropic PDEs [ 161) are available [q]. Choice of the appropriate method of relaxation, which can usually be determined by PDE inspection, is crucial in achieving rapid convergence. Block Gaussian elimination can be used to solve coarse-grid equations with two-dimensional nonseparable hybrid solvers. Deferred corrections [13] are used to improve second-order estimates to fourth order. Error control for convergence monitoring is included. Full multigrid cycling (FMG) is available [7] and eliminates the need for initial guesses. Exact minimal work-space requirements are output. Equivalencing can be used to save storage. The package includes extensive documentation and test programs which can be used for testing when installing the codes on new systems.

Recent Developments 3.

SOFTWARE

in

81

MUDPACK

CHANGES

(a) Multigrid Options The new version of MUDPACK includes options for those wishing to implement variants of multigrid iteration. This provides users familiar with multigrid the opportunity to experiment with and fine-tune the underlying algorithms for greater efficiency. Default options are retained for those preferring black-box solvers. This is accomplished with a integer vector, MGOET,

cycles

which sets the kind of cycling (e.g., F [ll], V, W, or more general can be selected), the number of pre- and post-coarse-grid-correction

relaxation sweeps, the method of residual restriction, and the method of prolongation. A listing describing MGOFT, as it appears in all solver documentation files, is contained in the Appendix. The new default multigrid options set W(2,l) cycling, fully weighted residual restriction, and cubic prolongation. These are more robust than V(2,l) cycling with linear prolongation, which were all that was available in the previous version of MUDPACK. The new default options increase computational time by at least 25% pr multigrid cycle in three dimensions and 50% in two dimensions. Nevertheless, they are more reliable and can give better overall efficiency (see Example A). V cycling with linear prolongation can still be selected as a possibly more efficient choice for certain problems. (19) Fourth-Order Fourth-order

Solvers solvers in two and three dimensions

are now available

that

use deferred corrections [13] to improve second-order estimates to fourthorder accuracy. We briefly review this technique in one dimension. The extension to higher dimensions is straightforward. Suppose we wish operator notation):

to solve

the

following

linear

elliptic

equation

(in

lu= f Using standard second-order finite-difference grid (of size h) yields the linear system LU= which we can solve to discretization-level truncation error t=F-Lu

approximations

on a uniform

F, error using multigrid

iteration.

The

82

JOHN C. ADAMS

measures

how closely

tion equations.

the exact continuous

Simple Taylor-series

t =

h’(

cu,,,

solution

arguments +

satisfies

the discretiza-

show that t has the form

dux,,,) + O( h-‘))

where c, d are known coefficients from the elliptic equation. If U satisfies the discretization equations exactly, then it can he used to generate second-order approximations to uXI, and u,,,,. For example, if the uniform grid on [u, b] is a=x(l)

< ...


< ..*


and U(i) is the approximation at x(i), then the following difference formula can be used to approximate the third and fourth partial derivatives of u(x): at x=a:

u,,,

=

u,,,,

=

-5U(

1) + lSU(2)

-24U(3)

+ 14U(4)

-3U(5)

zh”

+ O(h”),

3U(1)-14U(2)+26U(3)-24U(4)+11U(5)-2U(6)

+ O(h”);

h’

at x=a+h:

u,,,

=

-3U(l)

+ lOU(2)

- 12U(3)

+6U(4)

2h3 2U(1)-9U(2)+16U(3)-14U(4)+6U(5)-U(6)

UXX.r, =

h’

at x = x(i),

I.4XXX=

u,,,,

=

where

-U(5)

+ O(h”),

+ 0( h”);

a + h < x < b - h:

-U(i-2)+2u(i-l)-2u(i+l)+u(i+2)

+ 0( h”),

2hR U(i-2)-4U(i-l)+SU(i)-4U(i+l)+U(i+Z)

h”

+ 0( h”).

Recent Developments Similar

difference

in

83

MUDPACK

formulae

are used at x = b - h and x = 17. These

can be

obtained by using the FORTRAN difference-formula generators described in [4]. The necessary difference equations are encoded in the MCDPACK fourthorder solvers. If we denote all of these by the difference operators

S”( II) =

u,,,. +

S“(V) =

u,,,,

O( h’),

+ 0( h’)

and let

T = h"[

cS”( V) + &P(V)] ,

then

T=t+O(h’). The fourth-order truncation-error estimate T is computed and passed down to coarser grids using weighted averaging. Then one full multigrid cycle with the default options is used to solve the correction

equation

LE=-T. Since

E is an O(h”)

approximation

to the exact error

e=u--U=L_1(-t), it follows that V=V+E yields a fourth-order approximation in V. Another related and effective method for generating higher-order approximations with multigrid is r-extrapolation (see [7]). The use of higher-order stencils is investigated in [14]. Examples B, D in the next section illustrate the significant improvements in accuracy that the fourth-order solvers can provide at reasonable computational and storage costs.

84

JOHN C. ADAMS

(c) Grid Size Second- and fourth-order approximations are generated on uniform Iby-m-by-n grids superimposed on boxes in three dimensions or l-by-m grids superimposed on rectangles in two dimensions. The new grid sizes (including boundaries) have the form 1=p2’+1

m=92j+l n=r2k+l

(x-direction

size),

( y-direction

size),

(z-direction

size),

i,j, k > 0 and p, 9, r > 1 are integers. In the earlier version of i = j = k was required. Since p, 9, r should be small for effective error reduction with multigrid iteration, the old constraint was not well suited for asymmetric grid sizes (see Example C). Let G denote the Z-by-m-by-n fine grid. Multigrid iteration is implemented on the ascending chain of grids where

MUDPACK,

G(0) < ...


< -..

where t = max(i, j, k) and each G(s) n(s) grid points given by l(S)

m(s)

=

for s = 0,. .,t

p 2nw(s+i--t,O)

=q2

n(s) =r2


mnx(s

+

1,

+j-t,O) +

1,

max(s+k-t,O)

+

=G,

has Z(s) by m(s)

by

1.

The coarsest grid, G(O), has p + 1 by 9 + 1 by r + 1 points. p, 9, r should all be chosen as small as possible and i, j, k, as large as possible within grid-size constraints for effective error reduction with multigrid iteration. p, 9, and r should each be 2 or a small odd value, since even values greater than 2 can be reduced by increasing i, j, or k. Large values for p (9, r) can reduce the convergence rate even if line relaxation in the x (y, Z) direction is chosen (see Example D). Larger values for p or 9 cause no problem if one of the two-dimensional “hybrid’ solvers (discussed next) is used. The earlier MUDPACK requirement that p (9, r.) must be greater than 2 when line relaxation in the x (y, z) direction is used and the x (y, z) boundary condition is periodic has been removed.

Recent Developments in

85

MUDPACK

(d) Hybrid Soloers The certainty of direct methods is combined with the efficiency of solvers in MUDPACK. multigrid iteration in “hybrid” multigrid-direct-method This has been done for two-dimensional nonseparable elliptic equations. Separable PDEs can be approximated with cyclic reduction [6, 151if a direct method is required. The hybrid solvers use block Gaussian elimination whenever the coarsest grid level is encountered within multigrid cycling. This eliminates the constraint that p, y must be small and provides a natural way to compare solutions from direct and iterative schemes. In the extreme case of I = p + I and rn = y + 1, the hybrid codes become (storage permitting) direct-method solvers. The use of Gaussian elimination requires approximately 2(p + l)(p + l)(y + 1) additional words of storage if periodic boundary conditions are not set in the y direction, and approximately 4(p + l)(p + l)(y + 1) additional words of storage if they are. If there are n = I = m grid points in each direction, then balance between multigrid iteration, which is an O(n”) algorithm, and the direct method, which O(p”) operations for solution on the coarsest grid, is roughly requires achieved when

This holds when

kc-

grid levels

are used

before

log, n

switching

2 to the direct

method.

Choosing

p

approximately equal to n /Zk will achieve rough parity between the direct and iterative parts of the hybrid algorithm. Larger values for p mean the direct method will dominate the computation, while smaller values will only marginally 4.

increase

the cost of multigrid

iteration.

EXAMPLES

Examples A, B, C, and D illustrate the advantages of the revisions discussed in Section 3. All runs were done on a Cray Y-Mpg/S64 computer. The name of the MUDPACK solver used is included in each table. Initial guesses are not provided. The results for the fourth-order solvers assume a second-order solution has been computed. The minimum required storage (in megawords), the exact least-squares error, and the execution time and

JOHN C. ADAMS

86

megaflop rate for one full multigrid cycle are recorded in Examples D. Discretization times and other overhead are not measured.

B, C and

We present full-multigrid (FMG) reEXAXIPLLCIA (Multigrid options). sults when solving a two- and three-dimensional elliptic PDE with different multigrid options. For both problems, we determine the accuracy in the approximation generated after only one full multigrid cycle by computing

where II.11is the Euclidean

norm,

h is the mesh size in each coordinate uh is the exact multigrid cycles),

discrete

solution

direction, (generated

by executing

u is the approximation generated after one full multigrid u0 is the exact PDE solution evaluated on grid h.

numerous

cycle,

Values for E,, less than 2.00 are considered to be acceptable FMG results. We compare results using V(2,l) cycles with linear prolongation and W(2,l) cycles with cubic prolongation. For both problems, point relaxation and fully weighted residual restriction are used. First we consider the two-dimensional cross derivative term on the unit square:

+[(1+x”)(l+yL)11/2-$-

nonseparable

elliptic

xyu(x,y)

Assume u(x, y) is specified at the upper x and lower satisfies the mixed derivative boundary conditions

~+y$-y2u(o,Y)=P(Y)

at

PDE

with a

= r(x,y).

y boundaries

x=0

and

Recent Deoelopments

in

87

MUVPACK

TABLE

1

\11’1>2(:R(.ll'l.O-l~lhll:NSIOYAI.) E/t With V cycles

11 I

iK

1 GiY I I!,?. I %i

With W cycles

141.66

1.69

140.90

0.99

137.16

0.99

130.35

1.00

and

The exact

is used

solution

for testing,

and the results

We next consider

are tabulated

the three-dimensional

in Table

separable

1.

elliptic

PDE

a”u a% a’u ax”+dys+a-“-(“+“+“)U(“,E/,-_)=T(l,y,-) & on the unit cube

is used

grids

with

for testing.

with

Dirichlet

Results

2” + 1 points

boundary

are tabulated

in each

direction

TABLE 41uD3sP

h I

conditions.

in Table

The exact

2 on three-dimensional

for increasing

2

With W cycles

ii7

4.73

z1

7.15

1.01

r64

9.78

1.00

12.45

1.00

14.55

1.00

1 ii% 1 Ez

k.

(THREI~-~IMENSIONAL)

With V cycles

solution

1.04

JOHN C. ADAMS

88 TABLE 3 brun3sr (sEcOND-OKIER) Grid 17X17X17 33X33X33 65X65x65 129X129X129 257X257X257

Storage (Mwords)

Rate (Mflops)

Time (set>

Error

0.013 0.088 0.651 4.995 39.144

26 52 92 141 178

0.01 0.06 0.30 1.63 10.42

0.19E - 2 0.51F.-3 O.l3c-3 0.33E - 4 0.83E-5

For both problems, results are poor using V cycles with linear prolongation and excellent using W cycles with cubic prolongation. See [2] for several examples where FMG results are satisfactory using the less expensive V cycles.

EXAMPLE B (Fourth-order). We approximate the three-dimensional PDE in Example A with second- and fourth-order solvers (see Tables 3 and 4). The default multigrid options and point relaxation are used. Computation and storage of the fourth-order truncation-error estimate account for the reduced megaflop rate and additional expense with the fourth-order solver. If accuracy is measured as a function of computational expense, then the fourth-order scheme is very cost-effective. It achieves more accuracy on the 33 X33 x 33 grid than the second-order solver does on the 257X257 X257 grid. The fourth-order solver requires too much storage (approximately 56 Mwords) for solution on the highest-resolution grid. The error reductions, with each doubling of resolution, by a factor of 4 for second-order and a factor of 16 for fourth-order, verify that discretization-level error has been reached.

TABLE 4 ~cn34s~ (FOURTH-0~13313) Grid 17X17X17 33X33X33 65X65X65 129x129x129

Storage (Mwords)

Rate (Mflops)

Time (set)

0.018 0.124 0.926 7.142

19 35 72 98

0.03 0.16 0.62 3.76

Error 0.26~ 0.13E 0.78~ 0.47E

- 4 -5 - 7 - 8

Recent Developments EXAMPLE

C

(Grid

use more grid points than in the vertical horizontal

on the

than vertical

region

where z() boundary in x and derivative

BY

in MUDPACK

size).

Typically,

three-dimensional

resolution

in solving

solution

= 10 and xc, = y. = 2500, is used to set the right-hand side and conditions and to compute the error. Here we assume u is periodic y, specified at the lower z boundary, and satisfies the mixed condition

The PDE

coefficients

are given

a(x)

default

parameters are shown

models

the equation

0 < x, y < 10,000 km and 0 < z < 10 km. The exact

uz+u=h(x,y)

The

weather

in the horizontal direction, where the scales are larger, direction. To simulate this, we use eight times more

multigrid

options

at

z=lO.

by

=l+sin”(7rx/x,,),

and

are p = y = r = 3 and in Table 5.

point

relaxation

i = j = k +3

TABLE

are

selected.

for increasing

Grid

5

hlUlI3bP storage Grid size 49X49X7 97X97x

13

(Mwords)

Rate (Mflops)

Solution time (set)

size

k. The results

Error

0.057

37

0.058

0.46~ - 4

0.324

76

0.189

0.12E - 4

193X193x25

2.299

128

0.829

0.29~ - 5

395X395x49

17.271

193

4.633

0.77E - 6

JOHN C. ADAMS

90

EXAMPLE D (Hybrid solvers). Here we consider Helmholtz equation in spherical coordinates,

the two-dimensional

on a one-degree grid on the full surface of a sphere of radius 1 (4 and 0 are the longitude and colatitude). ~(6, 0) is specified at the poles 8 = 0,~ and is periodic in 4. For testing purposes, we use the exact solution

and the coefficient

functions o(4,e)

= A(4,e)

=s+sin’ecos”$.

Choosing p = 45, y = 45, i = 4, and j = 3 fits the required 361-by-181 grid exactly. Multigrid is implemented on the sequence of grid sizes 46X 46, 91 X 46, 181 X91, 361 X 181. One FMG cycle with the default multigrid options is executed. Both point relaxation and line relaxation in the 4 direction are used. Multigrid iteration with relaxation and Gaussian elimination on the 46-by-46 coarsest subgrid are compared. The results are shown in Table 6. There is a reduction in the megaflop rate with the hybrid method. Nevertheless, the results indicate that relaxation alone is ineffective in reducing error with the high-resolution coarse grid. In fact, if we use the most robust form of two-dimensional relaxation (lines in both the r$ and the 0 direction) at all grid levels, then 36 multigrid cycles and almost 4 seconds of computer time are required to reach discretization level error. In only one FMG is discretization-level error reached in less than i second, when the

TABLE 6 ~~1~2,~112, ~~~124

Method

Storage (Mwords)

Rate (Mflops)

Solution time (set)

Relax (point) Relax (line 4) Hybrid (point) Hybrid (line 4) Hybrid (fourth)

0.618 1.059 0.815 1.256 1.321

118 111 51 53 58

0.067 0.086 0.229 0.245 0.285

Error 0.73E 0.67~ 0.44E 0.43E 0.47~

-

2 2 5 5 8

Recent Developments in

91

MUDPACK

coarse-grid direct method is used with either point or line relaxation at the higher-resolution grids. For a small additional cost, the hybrid method improves the second-order estimate to a fourth-order approximation.

APPENDIX.

DOCUMENTATION

A listing of the multigrid documentation

FOR

MGOPT

options parameter

file for each second-order

~~:oPI’, as it appears

in the

solver, follows:

MUDPACK

C MGOPT c

AN

C

AMONG

C

A

C

WILL

C

ARE

C

GRID

C

INTEGER

VECTOR

VARIOUS

DEFAULT

SET

BE

OF

OF

5

AND

CORRECTION

ALLOWS

DEFINED

ALGORITHM

THE

USER

IF RGOPTcI)=o

PARAMETERS OTHERWISE

SELECTED.

INTERNALLY

WHICH

OPTIONS.

MULTIGRID

INTERNALLY

SET

LENGTH

MULTIGRID

AS

TO

IS

(CHOSEN FOR PARAMETERS

FOLLOWS:

(SEE

SELECT

INPUT

THEN

ROBUSTNESS) IN MGOPT

BASIC

COARSE

BELOW)

KCYCLE=MGOPTclI

C

=-1

C

=0

IF IF

DEFAULT

CKCYCLE

C

IS TO

F CYCLING

BE

MULTIGRID

WILL

BE

C

=I

IF V

C

=2

IF w CYCLING

CYCLING

OPTIONS

RESET IS

USED

TO

ARE

TO

BE

USED

2)

TO

BE

USED

(THE

LEAST

IS TO

BE

USED

(THE

DEFAULT)

EXPENSIVE

K

CYCLING

LARGER

THAN

PER

CYCLE)

C

C .GE.

3 IF

MORE

GENERAL

(WARNING--VALUES

C

C

THE

C

RESULT

EXECUTION

C

IPRER=MGOPTCZI

TIME

IN THE

C

THE

C

RESIDUAL

NUMBER IS

C

COARSER

GRID

PER

CYCLE

NON-FATAL

OF

IS 1

USED

INCREASE



AND

SWEEPS

CYCLING

(DEFAULT

AND

IERROR=-

.‘PRE-RELAXATION LEVEL

BE

2

CONSIDERABLY

ERROR

RESTRICTED

TO

OR

EXECUTED

IS

VALUE

IS

BEFORE

INVOKED 2

AT

WHENEVER

THE

THE NEXT

MGOPTcl)=O)

C C

IPOST=MGOPTc3)

C

THE

NUMBER

C

HAS

BEEN

C

CORRECTION

C

WHENEVER

C C

OF

“POST

INVOKED HAS

AT BEEN

RELAXATION THE

NEXT



SWEEPS

COARSER

TRANSFERRED

EXECUTED

GRID

BACK

AFTER

LEVEL

(DEFAULT

AND VALUE

CYCLING

THE IS

RESIDUAL 1

MGOPTcl)=O).

IRESW=MGOPTc4)

=O

IF UNWEIGHTED

C

(WARNING--ORDINARILY

C

WHEN

USED

(IDENTITY)

RESIDUAL THIS

WITHIN

MULTIGRID

OPTION

RESTRICTI?“S GIVES

POOR

ARE

USED

?‘iSULTS

ITERATION)

C C C C

=l

IF DEFAULT

FULLY

WEIGHTED VALUE

WHENEVER

RESIDUAL

RESTRICTIONS

MGOPTcl)=O).

ARE

USED

(THIS

IS

THE

92

JOHN =2

C

IF

HALF

C

(THIS

C

AND,

C

SIMILAR

WEIGHTING

OPTION

IS

USED

REQUIRES

WITH

WITH

LESS

RED/BLACK

POINT

CONVERGENCE

RESIDUAL

TIME

THAN

RESTRICTIONS. FULL

RELAXATION,

RATES.

IT

WEIGHTING

SOMETIMES

SHOULD

C. ADAMS

BE

GIVES

USED

WITH

CAUTION)

C C

INTPOL=MGOPTC5)

C =i

C

MULTILINEAR

IF

C

TRANSFER

C

FROM

PROLONGATION

RESIDUAL COARSE

(INTERPOLATION)

CORRECTIONS

TO

FINE

AND

GRIDS

THE

WITHIN

Is PDE

FULL

USED

TO

APPROXIMATION

MULTIGRID

CYCLING.

C C

3

IF

MULTICUBIC

C

TRANSFER

C

FROM

C

(THIS

PROLONGATION RESIDUAL

COARSE

TO

IS

THE

(INTERPOLATION)

CORRECTIONS FINE

AND

GRIDS

DEFAULT

WITHIN

VALUE

IS

THE

PDE

FULL

WHENEVER

USED

TO

APPROXIMATION

MULTIGRID

CYCLING.

MGOPTCl)=O).

C C

THE

DEFAULT

C

FOR

ROBUSTNESS.

C WILL

VALUES

GIVE

c

ONE

c

C1,2,1,1,1)

IN

GOOD

AN

(2,2,1,1,3) IN

SOME

RESULTS

EARLIER

THE

IN CASES

WITH

VC2,l) LESS

VERSION

OF

VECTOR

MGOPT

CYCLES

WITH

COMPUTATION.

MUDPACK)

WERE

THIS

CAN

BE

CHOSEN

LINEAR

PROLONGATION

CHOICE

SET

WITH

(THE

THE

ONLY

VECTOR

REFERENCES 1

J. Adams, linear

Multigrid

MUDPACK:

elliptic

partial

FORTRAN software

differential

equations,

for the efficient

Appl.

Math.

solution

of

34:113-146

Comput.

(1989). 2

J.

Adams,

FMG

Proceedings

results

of the Fourth

with

the

Copper

multigrid Mountain

software

package

Conference

in

~~UDFAC:K,

SIAM,

on Multigrid,

1989, pp 1-12. 3 4 5

J. Adams,

2.0, NCAR,

J. Adams,

Fortran

subprograms

for finite

difference

26:113-116

(1978).

J. Adams,

R. Garcia, of the

science,

B. Gross,

J, Hack,

multigrid

scientific

software

Partial

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V. Pizzo, and E. Ridley,

package

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partial

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Fortran

equations,

in

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D.

A Multigrid

Jespersen,

appear.

Tutorial,

Vectorization

Vieweg,

Multigrid

SIAM,

of Compuer

Soloers

problems,

Math.

and S. Parter,

Philadelphia Programs

1987.

with Applications

to Computa-

1984.

methods

for partial

Anal. 24, Math. Assoc. Amer.,

J. Mandel

for the

Problem

(1977).

tional Fluid Dynamics, Numer.

in atmo-

MUDPACK

(M. Schultz, Ed.), Academic, New York, 1982, pp. 333-390. A. Brandt, Multi-level adaptive solutions to boundary value

W. Gentzsch,

Phys.

in preparation.

solution

8

Differential

Mar. 1990. formula,

D. Haidvogel,

J. Adams, P. Swarztrauber,

9

11

Elliptic

Version

Comp. 31:333-390

10

for Linear

User Document

spheric

7

Software

SCD

Applications 6

Multigrid

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