Author: void
Date: Fri Aug 29 15:00:59 2014
New Revision: 216762
URL: http://llvm.org/viewvc/llvm-project?rev=216762&view=rev
Log:
Include blurb about Likely. By Josh Klontz.
Modified:
llvm/branches/release_35/ (props changed)
llvm/branches/release_35/docs/ReleaseNotes.rst
Propchange: llvm/branches/release_35/
------------------------------------------------------------------------------
--- svn:mergeinfo (original)
+++ svn:mergeinfo Fri Aug 29 15:00:59 2014
@@ -1,3 +1,3 @@
/llvm/branches/Apple/Pertwee:110850,110961
/llvm/branches/type-system-rewrite:133420-134817
-/llvm/trunk:155241,213653,213665,213726,213749,213773,213793,213798-213799,213815,213847,213880,213883-213884,213894-213896,213899,213915,213966,213999,214060,214129,214180,214287,214331,214423,214429,214519,214670,214674,214679,215685,215711,215806,216064
+/llvm/trunk:155241,213653,213665,213726,213749,213773,213793,213798-213799,213815,213847,213880,213883-213884,213894-213896,213899,213915,213966,213999,214060,214129,214180,214287,214331,214423,214429,214519,214670,214674,214679,215685,215711,215806,216064,216531
Modified: llvm/branches/release_35/docs/ReleaseNotes.rst
URL:
http://llvm.org/viewvc/llvm-project/llvm/branches/release_35/docs/ReleaseNotes.rst?rev=216762&r1=216761&r2=216762&view=diff
==============================================================================
--- llvm/branches/release_35/docs/ReleaseNotes.rst (original)
+++ llvm/branches/release_35/docs/ReleaseNotes.rst Fri Aug 29 15:00:59 2014
@@ -305,6 +305,21 @@ which ensure vector-friendly data layout
representation of the program. The project uses the LLVM infrastructure for
optimization and code generation.
+Likely
+------
+
+`Likely <http://www.liblikely.org>`_ is an embeddable just-in-time Lisp for
+image recognition and heterogenous architectures. Algorithms are just-in-time
+compiled using LLVMâs MCJIT infrastructure to execute on single or
+multi-threaded CPUs and potentially OpenCL SPIR or CUDA enabled GPUs. Likely
+exploits the observation that while image processing and statistical learning
+kernels must be written generically to handle any matrix datatype, at runtime
+they tend to be executed repeatedly on the same type. Likely also seeks to
+explore new optimizations for statistical learning algorithms by moving them
+from an offline model generation step to a compile-time simplification of a
+function (the learning algorithm) with constant arguments (the training set).
+
+
Additional Information
======================
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