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authorHans Wennborg <hans@hanshq.net>2015-08-27 02:27:03 +0300
committerHans Wennborg <hans@hanshq.net>2015-08-27 02:27:03 +0300
commit9ef11fa1fa2e05e24a16acbc50df4ad9029ae5f8 (patch)
tree725b38370f0810d3b456fd5c8cc33b80c684c656
parenta67b1c9d971d470ab94f34c7e105ee563c008ac6 (diff)
ReleaseNotes: fix some indentationllvmorg-3.7.0-rc4
llvm-svn: 246108
-rw-r--r--llvm/docs/ReleaseNotes.rst112
1 files changed, 56 insertions, 56 deletions
diff --git a/llvm/docs/ReleaseNotes.rst b/llvm/docs/ReleaseNotes.rst
index c61401feed6c..efceccce8199 100644
--- a/llvm/docs/ReleaseNotes.rst
+++ b/llvm/docs/ReleaseNotes.rst
@@ -286,89 +286,89 @@ Changes since the last release:
* isl imported into Polly distribution
-`isl <http://repo.or.cz/w/isl.git>`_, the math library Polly uses, has been
-imported into the source code repository of Polly and is now distributed as part
-of Polly. As this was the last external library dependency of Polly, Polly can
-now be compiled right after checking out the Polly source code without the need
-for any additional libraries to be pre-installed.
+ `isl <http://repo.or.cz/w/isl.git>`_, the math library Polly uses, has been
+ imported into the source code repository of Polly and is now distributed as part
+ of Polly. As this was the last external library dependency of Polly, Polly can
+ now be compiled right after checking out the Polly source code without the need
+ for any additional libraries to be pre-installed.
* Small integer optimization of isl
-The MIT licensed imath backend using in `isl <http://repo.or.cz/w/isl.git>`_ for
-arbitrary width integer computations has been optimized to use native integer
-operations for the common case where the operands of a computation fit into 32
-bit and to only fall back to large arbitrary precision integers for the
-remaining cases. This optimization has greatly improved the compile-time
-performance of Polly, both due to faster native operations also due to a
-reduction in malloc traffic and pointer indirections. As a result, computations
-that use arbitrary precision integers heavily have been speed up by almost 6x.
-As a result, the compile-time of Polly on the Polybench test kernels in the LNT
-suite has been reduced by 20% on average with compile time reductions between
-9-43%.
+ The MIT licensed imath backend using in `isl <http://repo.or.cz/w/isl.git>`_ for
+ arbitrary width integer computations has been optimized to use native integer
+ operations for the common case where the operands of a computation fit into 32
+ bit and to only fall back to large arbitrary precision integers for the
+ remaining cases. This optimization has greatly improved the compile-time
+ performance of Polly, both due to faster native operations also due to a
+ reduction in malloc traffic and pointer indirections. As a result, computations
+ that use arbitrary precision integers heavily have been speed up by almost 6x.
+ As a result, the compile-time of Polly on the Polybench test kernels in the LNT
+ suite has been reduced by 20% on average with compile time reductions between
+ 9-43%.
* Schedule Trees
-Polly now uses internally so-called > Schedule Trees < to model the loop
-structure it optimizes. Schedule trees are an easy to understand tree structure
-that describes a loop nest using integer constraint sets to keep track of
-execution constraints. It allows the developer to use per-tree-node operations
-to modify the loop tree. Programatic analysis that work on the schedule tree
-(e.g., as dependence analysis) also show a visible speedup as they can exploit
-the tree structure of the schedule and need to fall back to ILP based
-optimization problems less often. Section 6 of `Polyhedral AST generation is
-more than scanning polyhedra
-<http://www.grosser.es/#pub-polyhedral-AST-generation>`_ gives a detailed
-explanation of this schedule trees.
+ Polly now uses internally so-called > Schedule Trees < to model the loop
+ structure it optimizes. Schedule trees are an easy to understand tree structure
+ that describes a loop nest using integer constraint sets to keep track of
+ execution constraints. It allows the developer to use per-tree-node operations
+ to modify the loop tree. Programatic analysis that work on the schedule tree
+ (e.g., as dependence analysis) also show a visible speedup as they can exploit
+ the tree structure of the schedule and need to fall back to ILP based
+ optimization problems less often. Section 6 of `Polyhedral AST generation is
+ more than scanning polyhedra
+ <http://www.grosser.es/#pub-polyhedral-AST-generation>`_ gives a detailed
+ explanation of this schedule trees.
* Scalar and PHI node modeling - Polly as an analysis
-Polly now requires almost no preprocessing to analyse LLVM-IR, which makes it
-easier to use Polly as a pure analysis pass e.g. to provide more precise
-dependence information to non-polyhedral transformation passes. Originally,
-Polly required the input LLVM-IR to be preprocessed such that all scalar and
-PHI-node dependences are translated to in-memory operations. Since this release,
-Polly has full support for scalar and PHI node dependences and requires no
-scalar-to-memory translation for such kind of dependences.
+ Polly now requires almost no preprocessing to analyse LLVM-IR, which makes it
+ easier to use Polly as a pure analysis pass e.g. to provide more precise
+ dependence information to non-polyhedral transformation passes. Originally,
+ Polly required the input LLVM-IR to be preprocessed such that all scalar and
+ PHI-node dependences are translated to in-memory operations. Since this release,
+ Polly has full support for scalar and PHI node dependences and requires no
+ scalar-to-memory translation for such kind of dependences.
* Modeling of modulo and non-affine conditions
-Polly can now supports modulo operations such as A[t%2][i][j] as they appear
-often in stencil computations and also allows data-dependent conditional
-branches as they result e.g. from ternary conditions ala A[i] > 255 ? 255 :
-A[i].
+ Polly can now supports modulo operations such as A[t%2][i][j] as they appear
+ often in stencil computations and also allows data-dependent conditional
+ branches as they result e.g. from ternary conditions ala A[i] > 255 ? 255 :
+ A[i].
* Delinearization
-Polly now support the analysis of manually linearized multi-dimensional arrays
-as they result form macros such as
-"#define 2DARRAY(A,i,j) (A.data[(i) * A.size + (j)]". Similar constructs appear
-in old C code written before C99, C++ code such as boost::ublas, LLVM exported
-from Julia, Matlab generated code and many others. Our work titled
-`Optimistic Delinearization of Parametrically Sized Arrays
-<http://www.grosser.es/#pub-optimistic-delinerization>`_ gives details.
+ Polly now support the analysis of manually linearized multi-dimensional arrays
+ as they result form macros such as
+ "#define 2DARRAY(A,i,j) (A.data[(i) * A.size + (j)]". Similar constructs appear
+ in old C code written before C99, C++ code such as boost::ublas, LLVM exported
+ from Julia, Matlab generated code and many others. Our work titled
+ `Optimistic Delinearization of Parametrically Sized Arrays
+ <http://www.grosser.es/#pub-optimistic-delinerization>`_ gives details.
* Compile time improvements
-Pratik Bahtu worked on compile-time performance tuning of Polly. His work
-together with the support for schedule trees and the small integer optimization
-in isl notably reduced the compile time.
+ Pratik Bahtu worked on compile-time performance tuning of Polly. His work
+ together with the support for schedule trees and the small integer optimization
+ in isl notably reduced the compile time.
* Increased compute timeouts
-As Polly's compile time has been notabily improved, we were able to increase
-the compile time saveguards in Polly. As a result, the default configuration
-of Polly can now analyze larger loop nests without running into compile time
-restrictions.
+ As Polly's compile time has been notabily improved, we were able to increase
+ the compile time saveguards in Polly. As a result, the default configuration
+ of Polly can now analyze larger loop nests without running into compile time
+ restrictions.
* Export Debug Locations via JSCoP file
-Polly's JSCoP import/export format gained support for debug locations that show
-to the user the source code location of detected scops.
+ Polly's JSCoP import/export format gained support for debug locations that show
+ to the user the source code location of detected scops.
* Improved windows support
-The compilation of Polly on windows using cmake has been improved and several
-visual studio build issues have been addressed.
+ The compilation of Polly on windows using cmake has been improved and several
+ visual studio build issues have been addressed.
* Many bug fixes