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-rw-r--r--llvm/docs/DependenceGraphs/DDG.rst135
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-rw-r--r--llvm/docs/DependenceGraphs/cycle_pi.pngbin0 -> 47148 bytes
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-rw-r--r--llvm/docs/SubsystemDocumentation.rst6
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diff --git a/llvm/docs/DependenceGraphs/DDG.rst b/llvm/docs/DependenceGraphs/DDG.rst
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@@ -0,0 +1,135 @@
+=========================
+Dependence Graphs in LLVM
+=========================
+
+.. contents::
+ :local:
+
+Dependence graphs are useful tools in compilers for analyzing relationships
+between various program elements to help guide optimizations. The ideas
+behind these graphs are described in the following two papers:
+
+.. [1] "D. J. Kuck, R. H. Kuhn, D. A. Padua, B. Leasure, and M. Wolfe (1981). DEPENDENCE GRAPHS AND COMPILER OPTIMIZATIONS."
+.. [2] "J. FERRANTE (IBM), K. J. OTTENSTEIN (Michigan Technological University) and JOE D. WARREN (Rice University), 1987. The Program Dependence Graph and Its Use in Optimization."
+
+The implementation of these ideas in LLVM may be slightly different than
+what is mentioned in the papers. These differences are documented in
+the `implementation details <implementation-details_>`_.
+
+.. _DataDependenceGraph:
+
+Data Dependence Graph
+=====================
+In its simplest form the Data Dependence Graph (or DDG) represents data
+dependencies between individual instructions. Each node in such a graph
+represents a single instruction and is referred to as an "atomic" node.
+It is also possible to combine some atomic nodes that have a simple
+def-use dependency between them into larger nodes that contain multiple-
+instructions.
+
+As described in [1]_ the DDG uses graph abstraction to group nodes
+that are part of a strongly connected component of the graph
+into special nodes called pi-blocks. pi-blocks represent cycles of data
+dependency that prevent reordering transformations. Since any strongly
+connected component of the graph is a maximal subgraph of all the nodes
+that form a cycle, pi-blocks are at most one level deep. In other words,
+no pi-blocks are nested inside another pi-block, resulting in a
+hierarchical representation that is at most one level deep.
+
+
+For example, consider the following:
+
+.. code-block:: c++
+
+ for (int i = 1; i < n; i++) {
+ b[i] = c[i] + b[i-1];
+ }
+
+This code contains a statement that has a loop carried dependence on
+itself creating a cycle in the DDG. The figure bellow illustrates
+how the cycle of dependency is carried through multiple def-use relations
+and a memory access dependency.
+
+.. image:: cycle.png
+
+The DDG corresponding to this example would have a pi-block that contains
+all the nodes participating in the cycle, as shown bellow:
+
+.. image:: cycle_pi.png
+
+Program Dependence Graph
+========================
+
+The Program Dependence Graph (or PDG) has a similar structure as the
+DDG, but it is capable of representing both data dependencies and
+control-flow dependencies between program elements such as
+instructions, groups of instructions, basic blocks or groups of
+basic blocks.
+
+High-Level Design
+=================
+
+The DDG and the PDG are both directed graphs and they extend the
+``DirectedGraph`` class. Each implementation extends its corresponding
+node and edge types resulting in the inheritance relationship depicted
+in the UML diagram bellow:
+
+.. image:: uml_nodes_and_edges.png
+
+Graph Construction
+------------------
+
+The graph build algorithm considers dependencies between elements of
+a given set of instructions or basic blocks. Any dependencies coming
+into or going out of instructions that do not belong to that range
+are ignored. The steps in the build algorithm for the DDG are very
+similar to the steps in the build algorithm for the PDG. As such,
+one of the design goals is to reuse the build algorithm code to
+allow creation of both DDG and PDG representations while allowing
+the two implementations to define their own distinct and independent
+node and edge types. This is achieved by using the well-known builder
+design pattern to isolate the construction of the dependence graph
+from its concrete representation.
+
+The following UML diagram depicts the overall structure of the design
+pattern as it applies to the dependence graph implementation.
+
+.. image:: uml_builder_pattern.png
+
+Notice that the common code for building the two types of graphs are
+provided in the ``DependenceGraphBuilder`` class, while the ``DDGBuilder``
+and ``PDGBuilder`` control some aspects of how the graph is constructed
+by the way of overriding virtual methods defined in ``DependenceGraphBuilder``.
+
+Note also that the steps and the names used in this diagram are for
+illustrative purposes and may be different from those in the actual
+implementation.
+
+Design Trade-offs
+-----------------
+
+Advantages:
+^^^^^^^^^^^
+ - Builder allows graph construction code to be reused for DDG and PDG.
+ - Builder allows us to create DDG and PDG as separate graphs.
+ - DDG nodes and edges are completely disjoint from PDG nodes and edges allowing them to change easily and independently.
+
+Disadvantages:
+^^^^^^^^^^^^^^
+ - Builder may be perceived as over-engineering at first.
+ - There are some similarities between DDG nodes and edges compared to PDG nodes and edges, but there is little reuse of the class definitions.
+
+ - This is tolerable given that the node and edge types are fairly simple and there is little code reuse opportunity anyway.
+
+
+.. _implementation-details:
+
+Implementation Details
+======================
+
+The current implementation of DDG differs slightly from the dependence
+graph described in [1]_ in the following ways:
+
+ 1. The graph nodes in the paper represent three main program components, namely *assignment statements*, *for loop headers* and *while loop headers*. In this implementation, DDG nodes naturally represent LLVM IR instructions. An assignment statement in this implementation typically involves a node representing the ``store`` instruction along with a number of individual nodes computing the right-hand-side of the assignment that connect to the ``store`` node via a def-use edge. The loop header instructions are not represented as special nodes in this implementation because they have limited uses and can be easily identified, for example, through ``LoopAnalysis``.
+ 2. The paper describes five types of dependency edges between nodes namely *loop dependency*, *flow-*, *anti-*, *output-*, and *input-* dependencies. In this implementation *memory* edges represent the *flow-*, *anti-*, *output-*, and *input-* dependencies. However, *loop dependencies* are not made explicit, because they mainly represent association between a loop structure and the program elements inside the loop and this association is fairly obvious in LLVM IR itself.
+ 3. The paper describes two types of pi-blocks; *recurrences* whose bodies are SCCs and *IN* nodes whose bodies are not part of any SCC. In this impelmentation, pi-blocks are only created for *recurrences*. *IN* nodes remain as simple DDG nodes in the graph.
diff --git a/llvm/docs/DependenceGraphs/cycle.png b/llvm/docs/DependenceGraphs/cycle.png
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diff --git a/llvm/docs/SubsystemDocumentation.rst b/llvm/docs/SubsystemDocumentation.rst
index 005d541ceb3..463a17aa427 100644
--- a/llvm/docs/SubsystemDocumentation.rst
+++ b/llvm/docs/SubsystemDocumentation.rst
@@ -55,6 +55,7 @@ For API clients and LLVM developers.
SpeculativeLoadHardening
StackSafetyAnalysis
LoopTerminology
+ DataDependenceGraphs
:doc:`WritingAnLLVMPass`
Information on how to write LLVM transformations and analyses.
@@ -207,4 +208,7 @@ For API clients and LLVM developers.
variables.
:doc:`LoopTerminology`
- A document describing Loops and associated terms as used in LLVM. \ No newline at end of file
+ A document describing Loops and associated terms as used in LLVM.
+
+:doc:`DataDependenceGraphs`
+ A description of the design of the DDG (Data Dependence Graph).
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