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180 lines
9.0 KiB
HTML
4 years ago
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<html lang="en">
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<head>
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<title>Dependency analysis - GNU Compiler Collection (GCC) Internals</title>
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<meta http-equiv="Content-Type" content="text/html">
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<meta name="description" content="GNU Compiler Collection (GCC) Internals">
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<link title="Top" rel="start" href="index.html#Top">
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<link rel="up" href="Loop-Analysis-and-Representation.html#Loop-Analysis-and-Representation" title="Loop Analysis and Representation">
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<link rel="prev" href="Number-of-iterations.html#Number-of-iterations" title="Number of iterations">
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<link rel="next" href="Omega.html#Omega" title="Omega">
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Copyright (C) 1988-2015 Free Software Foundation, Inc.
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Permission is granted to copy, distribute and/or modify this document
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under the terms of the GNU Free Documentation License, Version 1.3 or
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any later version published by the Free Software Foundation; with the
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Invariant Sections being ``Funding Free Software'', the Front-Cover
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(see below). A copy of the license is included in the section entitled
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``GNU Free Documentation License''.
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(a) The FSF's Front-Cover Text is:
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A GNU Manual
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(b) The FSF's Back-Cover Text is:
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</head>
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<body>
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<div class="node">
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<a name="Dependency-analysis"></a>
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<p>
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Next: <a rel="next" accesskey="n" href="Omega.html#Omega">Omega</a>,
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Previous: <a rel="previous" accesskey="p" href="Number-of-iterations.html#Number-of-iterations">Number of iterations</a>,
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Up: <a rel="up" accesskey="u" href="Loop-Analysis-and-Representation.html#Loop-Analysis-and-Representation">Loop Analysis and Representation</a>
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<hr>
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</div>
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<h3 class="section">15.8 Data Dependency Analysis</h3>
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<p><a name="index-Data-Dependency-Analysis-3239"></a>
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The code for the data dependence analysis can be found in
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<samp><span class="file">tree-data-ref.c</span></samp> and its interface and data structures are
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described in <samp><span class="file">tree-data-ref.h</span></samp>. The function that computes the
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data dependences for all the array and pointer references for a given
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loop is <code>compute_data_dependences_for_loop</code>. This function is
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currently used by the linear loop transform and the vectorization
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passes. Before calling this function, one has to allocate two vectors:
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a first vector will contain the set of data references that are
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contained in the analyzed loop body, and the second vector will contain
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the dependence relations between the data references. Thus if the
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vector of data references is of size <code>n</code>, the vector containing the
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dependence relations will contain <code>n*n</code> elements. However if the
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analyzed loop contains side effects, such as calls that potentially can
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interfere with the data references in the current analyzed loop, the
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analysis stops while scanning the loop body for data references, and
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inserts a single <code>chrec_dont_know</code> in the dependence relation
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array.
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<p>The data references are discovered in a particular order during the
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scanning of the loop body: the loop body is analyzed in execution order,
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and the data references of each statement are pushed at the end of the
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data reference array. Two data references syntactically occur in the
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program in the same order as in the array of data references. This
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syntactic order is important in some classical data dependence tests,
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and mapping this order to the elements of this array avoids costly
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queries to the loop body representation.
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<p>Three types of data references are currently handled: ARRAY_REF,
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INDIRECT_REF and COMPONENT_REF. The data structure for the data reference
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is <code>data_reference</code>, where <code>data_reference_p</code> is a name of a
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pointer to the data reference structure. The structure contains the
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following elements:
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<ul>
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<li><code>base_object_info</code>: Provides information about the base object
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of the data reference and its access functions. These access functions
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represent the evolution of the data reference in the loop relative to
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its base, in keeping with the classical meaning of the data reference
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access function for the support of arrays. For example, for a reference
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<code>a.b[i][j]</code>, the base object is <code>a.b</code> and the access functions,
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one for each array subscript, are:
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<code>{i_init, + i_step}_1, {j_init, +, j_step}_2</code>.
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<li><code>first_location_in_loop</code>: Provides information about the first
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location accessed by the data reference in the loop and about the access
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function used to represent evolution relative to this location. This data
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is used to support pointers, and is not used for arrays (for which we
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have base objects). Pointer accesses are represented as a one-dimensional
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access that starts from the first location accessed in the loop. For
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example:
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<pre class="smallexample"> for1 i
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for2 j
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*((int *)p + i + j) = a[i][j];
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</pre>
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<p>The access function of the pointer access is <code>{0, + 4B}_for2</code>
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relative to <code>p + i</code>. The access functions of the array are
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<code>{i_init, + i_step}_for1</code> and <code>{j_init, +, j_step}_for2</code>
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relative to <code>a</code>.
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<p>Usually, the object the pointer refers to is either unknown, or we can't
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prove that the access is confined to the boundaries of a certain object.
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<p>Two data references can be compared only if at least one of these two
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representations has all its fields filled for both data references.
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<p>The current strategy for data dependence tests is as follows:
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If both <code>a</code> and <code>b</code> are represented as arrays, compare
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<code>a.base_object</code> and <code>b.base_object</code>;
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if they are equal, apply dependence tests (use access functions based on
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base_objects).
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Else if both <code>a</code> and <code>b</code> are represented as pointers, compare
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<code>a.first_location</code> and <code>b.first_location</code>;
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if they are equal, apply dependence tests (use access functions based on
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first location).
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However, if <code>a</code> and <code>b</code> are represented differently, only try
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to prove that the bases are definitely different.
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<li>Aliasing information.
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<li>Alignment information.
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</ul>
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<p>The structure describing the relation between two data references is
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<code>data_dependence_relation</code> and the shorter name for a pointer to
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such a structure is <code>ddr_p</code>. This structure contains:
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<ul>
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<li>a pointer to each data reference,
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<li>a tree node <code>are_dependent</code> that is set to <code>chrec_known</code>
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if the analysis has proved that there is no dependence between these two
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data references, <code>chrec_dont_know</code> if the analysis was not able to
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determine any useful result and potentially there could exist a
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dependence between these data references, and <code>are_dependent</code> is
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set to <code>NULL_TREE</code> if there exist a dependence relation between the
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data references, and the description of this dependence relation is
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given in the <code>subscripts</code>, <code>dir_vects</code>, and <code>dist_vects</code>
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arrays,
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<li>a boolean that determines whether the dependence relation can be
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represented by a classical distance vector,
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<li>an array <code>subscripts</code> that contains a description of each
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subscript of the data references. Given two array accesses a
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subscript is the tuple composed of the access functions for a given
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dimension. For example, given <code>A[f1][f2][f3]</code> and
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<code>B[g1][g2][g3]</code>, there are three subscripts: <code>(f1, g1), (f2,
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g2), (f3, g3)</code>.
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<li>two arrays <code>dir_vects</code> and <code>dist_vects</code> that contain
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classical representations of the data dependences under the form of
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direction and distance dependence vectors,
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<li>an array of loops <code>loop_nest</code> that contains the loops to
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which the distance and direction vectors refer to.
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</ul>
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<p>Several functions for pretty printing the information extracted by the
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data dependence analysis are available: <code>dump_ddrs</code> prints with a
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maximum verbosity the details of a data dependence relations array,
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<code>dump_dist_dir_vectors</code> prints only the classical distance and
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direction vectors for a data dependence relations array, and
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<code>dump_data_references</code> prints the details of the data references
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contained in a data reference array.
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</body></html>
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