COMPMID-765: Updated changelog for v18.02

Change-Id: Ib0378699a0c6d368d4e674eb914c9a62d1d86e14
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/121650
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Tested-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 34 insertions, 2 deletions

diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index c7faea7122..6de2d0f0e3 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -189,12 +189,42 @@ If there is more than one release in a month then an extra sequential number is
 
 @subsection S2_2_changelog Changelog
 
-v18.02 Public maintenance release
+v18.02 Public major release
+ - Various NEON / OpenCL / GLES optimisations.
+ - Various bug fixes.
+ - Changed default number of threads on big LITTLE systems.
+ - Refactored examples and added:
+    - graph_mobilenet_qassym8
+    - graph_resnet
+    - graph_squeezenet_v1_1
+ - Renamed @ref arm_compute::CLConvolutionLayer into @ref arm_compute::CLGEMMConvolutionLayer and created a new @ref arm_compute::CLConvolutionLayer to select the fastest convolution method.
+ - Renamed @ref arm_compute::NEConvolutionLayer into @ref arm_compute::NEGEMMConvolutionLayer and created a new @ref arm_compute::NEConvolutionLayer to select the fastest convolution method.
+ - Added in place support to:
+    - @ref arm_compute::CLActivationLayer
+    - @ref arm_compute::CLBatchNormalizationLayer
+ - Added QASYMM8 support to:
+    - @ref arm_compute::CLActivationLayer
+    - @ref arm_compute::CLDepthwiseConvolutionLayer
+    - @ref arm_compute::NEDepthwiseConvolutionLayer
+    - @ref arm_compute::NESoftmaxLayer
+ - Added FP16 support to:
+    - @ref arm_compute::CLDepthwiseConvolutionLayer3x3
+    - @ref arm_compute::CLDepthwiseConvolutionLayer
+ - Added broadcasting support to @ref arm_compute::NEArithmeticAddition / @ref arm_compute::CLArithmeticAddition / @ref arm_compute::CLPixelWiseMultiplication
+ - Added fused batched normalization and activation to @ref arm_compute::CLBatchNormalizationLayer and @ref arm_compute::NEBatchNormalizationLayer
+ - Added support for non-square pooling to @ref arm_compute::NEPoolingLayer and @ref arm_compute::CLPoolingLayer
+ - New OpenCL kernels / functions:
+    - @ref arm_compute::CLDirectConvolutionLayerOutputStageKernel
  - New NEON kernels / functions
+    - Added name() method to all kernels.
+    - Added support for Winograd 5x5.
+    - @ref arm_compute::NEPermuteKernel / @ref arm_compute::NEPermute
     - @ref arm_compute::NEWinogradLayerTransformInputKernel / @ref arm_compute::NEWinogradLayer
     - @ref arm_compute::NEWinogradLayerTransformOutputKernel / @ref arm_compute::NEWinogradLayer
     - @ref arm_compute::NEWinogradLayerTransformWeightsKernel / @ref arm_compute::NEWinogradLayer
     - Renamed arm_compute::NEWinogradLayerKernel into @ref arm_compute::NEWinogradLayerBatchedGEMMKernel
+ - New GLES kernels / functions:
+    - @ref arm_compute::GCTensorShiftKernel / @ref arm_compute::GCTensorShift
 
 v18.01 Public maintenance release
  - Various bug fixes
@@ -454,7 +484,7 @@ To see the build options available simply run ```scons -h```:
 		default: linux
 		actual: linux
 
-	build: Build type (native|cross_compile)
+	build: Build type (native|cross_compile|embed_only)
 		default: cross_compile
 		actual: cross_compile
 
@@ -532,6 +562,8 @@ To see the build options available simply run ```scons -h```:
 
 @note If you want to natively compile for 32bit on a 64bit ARM device running a 64bit OS then you will have to use cross-compile too.
 
+There is also an 'embed_only' option which will generate all the .embed files for the OpenCL kernels and / or OpenGLES compute shaders. This might be useful if using a different build system to compile the library.
+
 @b Werror: If you are compiling using the same toolchains as the ones used in this guide then there shouldn't be any warning and therefore you should be able to keep Werror=1. If with a different compiler version the library fails to build because of warnings interpreted as errors then, if you are sure the warnings are not important, you might want to try to build with Werror=0 (But please do report the issue either on Github or by an email to developer@arm.com so that the issue can be addressed).
 
 @b opencl / @b neon / @b gles_compute: Choose which SIMD technology you want to target. (NEON for ARM Cortex-A CPUs or OpenCL / GLES_COMPUTE for ARM Mali GPUs)