docs: Clean up adornments.

For whatever reason the usage of '^^^' and '---' adornments were
reversed compared to the "canonical" style of the LLVM docs (which is
currently "the style used in SphinxQuickstartTemplate.rst"). This change
doesn't affect the document structure at all, I'm just doing it for
trivial stylistic consistency (the document content is *much* more
important---thanks Nadav for writing this up!).

Also, trim the adornments to be the same length as the section names.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@170638 91177308-0d34-0410-b5e6-96231b3b80d8

diff --git a/docs/Vectorizers.rst b/docs/Vectorizers.rst
index 98f1451d0de14320ce987895894c8e5cc190d247..4a85a7ee6db8618582c478951539330ac397b983 100644 (file)
--- a/docs/Vectorizers.rst
+++ b/docs/Vectorizers.rst
@@ -13,7 +13,7 @@ The Loop Vectorizer
 ===================
 
 Usage
-^^^^^^
+-----
 
 LLVM's Loop Vectorizer is now available and will be useful for many people.
 It is not enabled by default, but can be enabled through clang using the
@@ -30,13 +30,13 @@ will only vectorize loops that do not require a major increase in code size.
 We plan to enable the Loop Vectorizer by default as part of the LLVM 3.3 release.
 
 Features
-^^^^^^^^^
+--------
 
 The LLVM Loop Vectorizer has a number of features that allow it to vectorize
 complex loops.
 
 Loops with unknown trip count
-------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 The Loop Vectorizer supports loops with an unknown trip count.
 In the loop below, the iteration ``start`` and ``finish`` points are unknown,
@@ -53,7 +53,7 @@ a scalar copy of the loop increases the code size.
   }
 
 Runtime Checks of Pointers
---------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 In the example below, if the pointers A and B point to consecutive addresses,
 then it is illegal to vectorize the code because some elements of A will be
@@ -75,7 +75,7 @@ of the loop is executed.
 
 
 Reductions
---------------------------
+^^^^^^^^^^
 
 In this example the ``sum`` variable is used by consecutive iterations of 
 the loop. Normally, this would prevent vectorization, but the vectorizer can
@@ -94,7 +94,7 @@ reduction operations, such as addition, multiplication, XOR, AND and OR.
   }
 
 Inductions
---------------------------
+^^^^^^^^^^
 
 In this example the value of the induction variable ``i`` is saved into an
 array. The Loop Vectorizer knows to vectorize induction variables.
@@ -107,7 +107,7 @@ array. The Loop Vectorizer knows to vectorize induction variables.
   }
 
 If Conversion
---------------------------
+^^^^^^^^^^^^^
 
 The Loop Vectorizer is able to "flatten" the IF statement in the code and
 generate a single stream of instructions. The Loop Vectorizer supports any
@@ -125,7 +125,7 @@ nesting of IFs, ELSEs and even GOTOs.
   }
 
 Pointer Induction Variables
----------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 This example uses the "accumulate" function of the standard c++ library. This
 loop uses C++ iterators, which are pointers, and not integer indices.
@@ -139,7 +139,7 @@ this loop. This feature is important because many C++ programs use iterators.
   }
 
 Reverse Iterators
---------------------------
+^^^^^^^^^^^^^^^^^
 
 The Loop Vectorizer can vectorize loops that count backwards.
 
@@ -151,7 +151,7 @@ The Loop Vectorizer can vectorize loops that count backwards.
   }
 
 Scatter / Gather
-----------------
+^^^^^^^^^^^^^^^^
 
 The Loop Vectorizer can vectorize code that becomes scatter/gather 
 memory accesses. 
@@ -164,7 +164,7 @@ memory accesses.
   }
 
 Vectorization of Mixed Types
-----------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 The Loop Vectorizer can vectorize programs with mixed types. The Vectorizer
 cost model can estimate the cost of the type conversion and decide if
@@ -178,7 +178,7 @@ vectorization is profitable.
   }
 
 Vectorization of function calls
--------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 The Loop Vectorize can vectorize intrinsic math functions.
 See the table below for a list of these functions.
@@ -196,7 +196,7 @@ See the table below for a list of these functions.
 +-----+-----+---------+
 
 Performance
-^^^^^^^^^^^
+-----------
 
 This section shows the the execution time of Clang on a simple benchmark: 
 `gcc-loops <http://llvm.org/viewvc/llvm-project/test-suite/trunk/SingleSource/UnitTests/Vectorizer/>`_.
@@ -212,7 +212,7 @@ The Basic Block Vectorizer
 ==========================
 
 Usage
-^^^^^^
+------
 
 The Basic Block Vectorizer is not enabled by default, but it can be enabled
 through clang using the command line flag:
@@ -222,7 +222,7 @@ through clang using the command line flag:
    $ clang -fslp-vectorize file.c 
 
 Details
-^^^^^^^
+-------
 
 The goal of basic-block vectorization (a.k.a. superword-level parallelism) is
 to combine similar independent instructions within simple control-flow regions