]> https://gitweb.dealii.org/ - dealii-svn.git/commitdiff
Doxygenize
authorwolf <wolf@0785d39b-7218-0410-832d-ea1e28bc413d>
Tue, 28 Mar 2006 15:22:06 +0000 (15:22 +0000)
committerwolf <wolf@0785d39b-7218-0410-832d-ea1e28bc413d>
Tue, 28 Mar 2006 15:22:06 +0000 (15:22 +0000)
git-svn-id: https://svn.dealii.org/trunk@12723 0785d39b-7218-0410-832d-ea1e28bc413d

14 files changed:
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/intro.dox [moved from deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/intro.html with 96% similarity]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/results.dox [moved from deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/results.html with 89% similarity]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-grid.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-partition.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-ux.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-uy.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-4-3d-partition.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-4-3d-ux.png [deleted file]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.12-grid.png [new file with mode: 0644]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.12-partition.png [new file with mode: 0644]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.12-ux.png [new file with mode: 0644]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.12-uy.png [new file with mode: 0644]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.4-3d-partition.png [new file with mode: 0644]
deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/step-17.4-3d-ux.png [new file with mode: 0644]

similarity index 96%
rename from deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/intro.html
rename to deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/intro.dox
index 3921f1f19b05295403255d00ca7c9799d79ca5b3..db168de9c3c91b06a811fffcc324079b481daf23 100644 (file)
@@ -1,9 +1,9 @@
 <a name="Intro"></a>
 <h1>Introduction</h1>
 
-<p>
+
 This program does not introduce any new mathematical ideas; in fact, all it
-does is to do the exact same computations that <a href="step-8.html">step-8</a>
+does is to do the exact same computations that @ref step_8 "step-8"
 already does, but it does so in a different manner: instead of using deal.II's
 own linear algebra classes, we build everything on top of classes deal.II
 provides that wrap around the linear algebra implementation of the <a
@@ -12,18 +12,18 @@ since PETSc allows to distribute matrices and vectors across several computers
 within an MPI network, the resulting code will even be able to solve the
 problem in parallel. If you don't know what PETSc is, then this would be a
 good time to take a quick glimpse at their homepage.
-</p>
 
-<p>
+
+
 As a prerequisite of this program, you need to have PETSc installed, and if
 you want to run in parallel on a cluster, you also need <a
 href="http://www-users.cs.umn.edu/~karypis/metis/index.html"
 target="_top">METIS</a> to partition meshes. The installation of deal.II
 together with these two additional libraries is described in the <a
 href="../../readme.html" target="body">README</a> file.
-</p>
 
-<p>
+
+
 Now, for the details: as mentioned, the program does not compute anything new,
 so the use of finite element classes etc. is exactly the same as before. The
 difference to previous programs is that we have replaced almost all uses of
@@ -40,18 +40,18 @@ functionality themselves, they simply pass on to their corresponding PETSc
 functions. The wrappers are therefore only used to give PETSc a more modern,
 object oriented interface, and to make the use of PETSc and deal.II objects as
 interchangable as possible.
-</p>
 
-<p>
+
+
 While the sequential PETSc wrappers classes do not have any advantage over
 their deal.II counterparts, the main point of using PETSc is that it can run
 in parallel. We will make use of this by partitioning the domain into as many
 blocks (``subdomains'') as there are processes in the MPI network. At the same
 time, PETSc provides dummy MPI stubs that allow to run the same program on a
 single machine if so desired, without any changes.
-</p>
 
-<p>
+
+
 Note, however, that the only data structures we parallelize are matrices and
 vectors. We do, in particular, not split up the <code>Triangulation</code> and
 <code>DoFHandler</code> classes: each process still has a complete copy of
@@ -62,12 +62,12 @@ present. It also requires that many more aspects of the application program
 have to be changed, since for example loops over all cells can only include
 locally available cells. We thus went for the path of least resistance and
 only parallelized the linear algebra part.
-</p>
 
-<p>
+
+
 The techniques this program demonstrates are: how to use the PETSc wrapper
 classes; how to parallelize operations for jobs running on an MPI network; and
 how to partition the domain into subdomains to parallelize up the work. Since
 all this can only be demonstrated using actual code, let us go straight to the
 code without much further ado.
-</p>
+
similarity index 89%
rename from deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/results.html
rename to deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/results.dox
index b101786ad2854f0ea4e2c1ce1df3fdc1135eeaaf..fbcf5be57ce5a088d2b15e73a73ca24310896e44 100644 (file)
@@ -1,7 +1,7 @@
 <a name="Results"></a>
 <h1>Results</h1>
 
-<p>
+
 If the program above is compiled and run on a single processor machine, it
 should generate results that are very similar to those that we already got
 with step-8. However, it becomes more interesting if we run it on a cluster of
@@ -11,7 +11,7 @@ have different calling syntaxes - on my system, I have to use the command
 that the exact command line syntax varies. If you have found out how to run a
 job on your system, you should get output like this for a job on 8 processors,
 and with a few more refinement cycles than in the code above:
-<code><pre>
+@code
 Cycle 0:
    Number of active cells:       64
    Number of degrees of freedom: 162 (by partition: 22+22+20+20+18+16+20+24)
@@ -81,10 +81,10 @@ Cycle 16:
    Number of degrees of freedom: 3771884 (by partition: 468452+474204+470818+470884+469960+
 471186+470686+475694)
    Solver converged in 2251 iterations.
-</pre></code>
-</p>
+@endcode
+
+
 
-<p>
 As can be seen, we can easily get to almost four million unknowns. In fact, the
 code's runtime with 8 processes was less than 7 minutes up to (and including)
 cycle 14, and 14 minutes including the second to last step. I lost the timing
@@ -99,37 +99,28 @@ although matrices and vectors are split up. For the 7.1M computation, the memory
 consumption was about 600 bytes per unknown, which is not bad, but one has to 
 consider that this is for every unknown, whether we store the matrix and vector
 entries locally or not.
-</p>
 
-<p>
+
+
 Here is some output generated in the 12th cycle of the program, i.e. with roughly
 300,000 unknowns:
-</p>
 
-<p align="center">
-  <a href="step-17.data/solution-12-ux.png" target="_top"><img
-  src="step-17.data/solution-12-ux.png" alt="ux" width="45%"></a>
-  <a href="step-17.data/solution-12-uy.png" target="_top"><img
-  src="step-17.data/solution-12-uy.png" alt="uy" width="45%"></a>
-</p>
 
-<p>
+@image html step-17.12-ux.png
+@image html step-17.12-uy.png
+
+
+
 As one would hope for, the x- (left) and y-displacements (right) shown here
 closely match what we already saw in step-8. What may be more interesting,
 though, is to look at the mesh and partition at this step (to see the picture
 in its original size, simply click on it):
-</p>
 
 
-<p align="center">
-  <a href="step-17.data/solution-12-grid.png" target="_top"><img
-  src="step-17.data/solution-12-grid.png" alt="grid" width="45%"></a>
-  <a href="step-17.data/solution-12-partition.png" target="_top"><img
-  src="step-17.data/solution-12-partition.png" alt="partition"
-  width="45%"></a>
-</p>
+@image html step-17.12-grid.png
+@image html step-17.12-partition.png
+
 
-<p>
 Again, the mesh (left) shows the same refinement pattern as seen
 previously. The right panel shows the partitioning of the domain across the 8
 processes, each indicated by a different color. The picture shows that the
@@ -138,9 +129,9 @@ expected given that the partitioning algorithm tries to equilibrate the number
 of cells in each subdomain; this equilibration is also easily identified in
 the output shown above, where the number of degrees per subdomain is roughly
 the same.
-</p>
 
-<p>
+
+
 It is worth noting that if we ran the same program with a different number of
 processes, that we would likely get slightly different output: a different
 mesh, different number of unknowns and iterations to convergence. The reason
@@ -153,22 +144,22 @@ preconditioner leads to slight changes in the computed solution, this will
 then lead to slightly different mesh cells tagged for refinement, and larger
 differences in subsequent steps. The solution will always look very similar,
 though.
-</p>
 
-<p>
+
+
 Finally, here are some results for a 3d simulation. You can repeat these by
 first changing
-<code><pre>
+@code
         ElasticProblem<2> elastic_problem;
-</pre></code>
+@endcode
 to
-<code><pre>
+@code
         ElasticProblem<3> elastic_problem;
-</pre></code>
+@endcode
 in the main function, and then in the Makefile, change the reference to the 2d
 libraries to their 3d counterparts. If you then run the program in parallel,
 you get something similar to this (this is for a job with 16 processes):
-<code><pre>
+@code
 Cycle 0:
    Number of active cells:       512
    Number of degrees of freedom: 2187 (by partition: 114+156+150+114+114+210+105+102+120+120+96+123+141+183+156+183)
@@ -197,25 +188,21 @@ Cycle 6:
    Number of active cells:       461392
    Number of degrees of freedom: 1497951 (by partition: 103587+100827+97611+93726+93429+88074+95892+88296+96882+93000+87864+90915+92232+86931+98091+90594)
    Solver converged in 261 iterations.
-</pre></code>
-</p>
+@endcode
+
+
 
-<p>
 The last step, going up to 1.5 million unknowns, takes about 55 minutes with
 16 processes on 8 dual-processor machines. The graphical output generated by
 this job is rather large (cycle 5 already prints around 82 MB of GMV data), so
 we contend ourselves with showing output from cycle 4 (again, clicking on the
 picture gives a version in original size):
-</p>
 
-<p align="center">
-  <a href="step-17.data/solution-4-3d-partition.png" target="_top"><img
-  src="step-17.data/solution-4-3d-partition.png" alt="uy" width="45%"></a>
-  <a href="step-17.data/solution-4-3d-ux.png" target="_top"><img
-  src="step-17.data/solution-4-3d-ux.png" alt="ux" width="45%"></a>
-</p>
 
-<p>
+@image html step-17.4-3d-partition.png
+@image html step-17.4-3d-ux.png
+
+
 The left picture shows the partitioning of the cube into 16 processes, whereas
 the right one shows the x-displacement along two cutplanes through the cube.
-</p>
+
diff --git a/deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-grid.png b/deal.II/doc/tutorial/chapter-2.step-by-step/step-17.data/solution-12-grid.png
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