Blame - docs/00_introduction.dox - ml/ComputeLibrary

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Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	1	/** @mainpage Introduction
				2
				3	@tableofcontents
				4
				5	The Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies.
				6
				7	Several builds of the library are available using various configurations:
				8	- OS: Linux, Android or bare metal.
				9	- Architecture: armv7a (32bit) or arm64-v8a (64bit)
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	10	- Technology: NEON / OpenCL / GLES_COMPUTE / NEON and OpenCL and GLES_COMPUTE
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	11	- Debug / Asserts / Release: Use a build with asserts enabled to debug your application and enable extra validation. Once you are sure your application works as expected you can switch to a release build of the library for maximum performance.
				12
				13	@section S0_1_contact Contact / Support
				14
				15	Please email developer@arm.com
				16
				17	In order to facilitate the work of the support team please provide the build information of the library you are using. To get the version of the library you are using simply run:
				18
				19	$ strings android-armv7a-cl-asserts/libarm_compute.so \| grep arm_compute_version
				20	arm_compute_version=v16.12 Build options: {'embed_kernels': '1', 'opencl': '1', 'arch': 'armv7a', 'neon': '0', 'asserts': '1', 'debug': '0', 'os': 'android', 'Werror': '1'} Git hash=f51a545d4ea12a9059fe4e598a092f1fd06dc858
				21
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	22	@section S0_2_prebuilt_binaries Pre-built binaries
				23
				24	For each release we provide some pre-built binaries of the library [here](https://github.com/ARM-software/ComputeLibrary/releases)
				25
				26	These binaries have been built using the following toolchains:
				27	- Linux armv7a: gcc-linaro-arm-linux-gnueabihf-4.9-2014.07_linux
				28	- Linux arm64-v8a: gcc-linaro-4.9-2016.02-x86_64_aarch64-linux-gnu
				29	- Android armv7a: clang++ / gnustl NDK r14
				30	- Android am64-v8a: clang++ / gnustl NDK r14
				31
				32	@warning Make sure to use a compatible toolchain to build your application or you will get some std::bad_alloc errors at runtime.
				33
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	34	@section S1_file_organisation File organisation
				35
				36	This archive contains:
				37	- The arm_compute header and source files
				38	- The latest Khronos OpenCL 1.2 C headers from the <a href="https://www.khronos.org/registry/cl/">Khronos OpenCL registry</a>
				39	- The latest Khronos cl2.hpp from the <a href="https://www.khronos.org/registry/cl/">Khronos OpenCL registry</a> (API version 2.1 when this document was written)
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	40	- The latest Khronos OpenGL ES 3.1 C headers from the <a href="https://www.khronos.org/registry/gles/">Khronos OpenGL ES registry</a>
				41	- The latest Khronos EGL 1.5 C headers from the <a href="https://www.khronos.org/registry/gles/">Khronos EGL registry</a>
				42	- The sources for a stub version of libOpenCL.so, libGLESv1_CM.so, libGLESv2.so and libEGL.so to help you build your application.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	43	- An examples folder containing a few examples to compile and link against the library.
				44	- A @ref utils folder containing headers with some boiler plate code used by the examples.
				45	- This documentation.
				46
				47	You should have the following file organisation:
				48
				49	.
				50	├── arm_compute --> All the arm_compute headers
				51	│ ├── core
				52	│ │ ├── CL
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	53	│ │ │ ├── CLKernelLibrary.h --> Manages all the OpenCL kernels compilation and caching, provides accessors for the OpenCL Context.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	54	│ │ │ ├── CLKernels.h --> Includes all the OpenCL kernels at once
				55	│ │ │ ├── CL specialisation of all the generic objects interfaces (ICLTensor, ICLImage, etc.)
				56	│ │ │ ├── kernels --> Folder containing all the OpenCL kernels
				57	│ │ │ │ └── CL*Kernel.h
				58	│ │ │ └── OpenCL.h --> Wrapper to configure the Khronos OpenCL C++ header
				59	│ │ ├── CPP
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	60	│ │ │ ├── CPPKernels.h --> Includes all the CPP kernels at once
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	61	│ │ │ └── kernels --> Folder containing all the CPP kernels
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	62	│ │ │ └── CPP*Kernel.h
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	63	│ │ ├── GLES_COMPUTE
				64	│ │ │ ├── GCKernelLibrary.h --> Manages all the GLES kernels compilation and caching, provides accessors for the GLES Context.
				65	│ │ │ ├── GCKernels.h --> Includes all the GLES kernels at once
				66	│ │ │ ├── GLES specialisation of all the generic objects interfaces (IGCTensor, IGCImage, etc.)
				67	│ │ │ ├── kernels --> Folder containing all the GLES kernels
				68	│ │ │ │ └── GC*Kernel.h
				69	│ │ │ └── OpenGLES.h --> Wrapper to configure the Khronos EGL and OpenGL ES C header
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	70	│ │ ├── NEON
				71	│ │ │ ├── kernels --> Folder containing all the NEON kernels
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	72	│ │ │ │ ├── arm64 --> Folder containing the interfaces for the assembly arm64 NEON kernels
				73	│ │ │ │ ├── arm32 --> Folder containing the interfaces for the assembly arm32 NEON kernels
				74	│ │ │ │ ├── assembly --> Folder containing the NEON assembly routines.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	75	│ │ │ │ └── NE*Kernel.h
				76	│ │ │ └── NEKernels.h --> Includes all the NEON kernels at once
				77	│ │ ├── All common basic types (Types.h, Window, Coordinates, Iterator, etc.)
				78	│ │ ├── All generic objects interfaces (ITensor, IImage, etc.)
				79	│ │ └── Objects metadata classes (ImageInfo, TensorInfo, MultiImageInfo)
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	80	│ ├── graph
				81	│ │ ├── CL --> OpenCL specific operations
				82	│ │ │ └── CLMap.h / CLUnmap.h
				83	│ │ ├── nodes
				84	│ │ │ └── The various nodes supported by the graph API
				85	│ │ ├── Nodes.h --> Includes all the Graph nodes at once.
				86	│ │ └── Graph objects ( INode, ITensorAccessor, Graph, etc.)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	87	│ └── runtime
				88	│ ├── CL
				89	│ │ ├── CL objects & allocators (CLArray, CLImage, CLTensor, etc.)
				90	│ │ ├── functions --> Folder containing all the OpenCL functions
				91	│ │ │ └── CL*.h
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	92	│ │ ├── CLScheduler.h --> Interface to enqueue OpenCL kernels and get/set the OpenCL CommandQueue and ICLTuner.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	93	│ │ └── CLFunctions.h --> Includes all the OpenCL functions at once
				94	│ ├── CPP
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	95	│ │ ├── CPPKernels.h --> Includes all the CPP functions at once.
				96	│ │ └── CPPScheduler.h --> Basic pool of threads to execute CPP/NEON code on several cores in parallel
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	97	│ ├── GLES_COMPUTE
				98	│ │ ├── GLES objects & allocators (GCArray, GCImage, GCTensor, etc.)
				99	│ │ ├── functions --> Folder containing all the GLES functions
				100	│ │ │ └── GC*.h
				101	│ │ ├── GCScheduler.h --> Interface to enqueue GLES kernels and get/set the GLES CommandQueue.
				102	│ │ └── GCFunctions.h --> Includes all the GLES functions at once
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	103	│ ├── NEON
				104	│ │ ├── functions --> Folder containing all the NEON functions
				105	│ │ │ └── NE*.h
				106	│ │ └── NEFunctions.h --> Includes all the NEON functions at once
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	107	│ ├── OMP
				108	│ │ └── OMPScheduler.h --> OpenMP scheduler (Alternative to the CPPScheduler)
				109	│ ├── Memory manager files (LifetimeManager, PoolManager, etc.)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	110	│ └── Basic implementations of the generic object interfaces (Array, Image, Tensor, etc.)
				111	├── documentation
				112	│ ├── index.xhtml
				113	│ └── ...
				114	├── documentation.xhtml -> documentation/index.xhtml
				115	├── examples
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	116	│ ├── cl_*.cpp --> OpenCL examples
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	117	│ ├── gc_*.cpp --> GLES compute shaders examples
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	118	│ ├── graph_*.cpp --> Graph examples
				119	│ ├── neoncl_*.cpp --> NEON / OpenCL interoperability examples
				120	│ └── neon_*.cpp --> NEON examples
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	121	├── include
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	122	│ ├── CL
				123	│ │ └── Khronos OpenCL C headers and C++ wrapper
				124	│ ├── half --> FP16 library available from http://half.sourceforge.net
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	125	│ ├── libnpy --> Library to load / write npy buffers, available from https://github.com/llohse/libnpy
				126	│ └── linux --> Headers only needed for Linux builds
				127	│ └── Khronos EGL and OpenGLES headers
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	128	├── opencl-1.2-stubs
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	129	│ └── opencl_stubs.c --> OpenCL stubs implementation
				130	├── opengles-3.1-stubs
				131	│ ├── EGL.c --> EGL stubs implementation
				132	│ └── GLESv2.c --> GLESv2 stubs implementation
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	133	├── scripts
				134	│ ├── caffe_data_extractor.py --> Basic script to export weights from Caffe to npy files
				135	│ └── tensorflow_data_extractor.py --> Basic script to export weights from Tensor Flow to npy files
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	136	├── src
				137	│ ├── core
				138	│ │ └── ... (Same structure as headers)
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	139	│ │ ├── CL
				140	│ │ │ └── cl_kernels --> All the OpenCL kernels
				141	│ │ └── GLES_COMPUTE
				142	│ │ └── cs_shaders --> All the OpenGL ES Compute Shaders
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	143	│ ├── graph
				144	│ │ └── ... (Same structure as headers)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	145	│ └── runtime
				146	│ └── ... (Same structure as headers)
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	147	├── support
				148	│ └── Various headers to work around toolchains / platform issues.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	149	├── tests
				150	│ ├── All test related files shared between validation and benchmark
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	151	│ ├── CL --> OpenCL accessors
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	152	│ ├── GLES_COMPUTE --> GLES accessors
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	153	│ ├── NEON --> NEON accessors
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	154	│ ├── benchmark --> Sources for benchmarking
				155	│ │ ├── Benchmark specific files
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	156	│ │ ├── CL --> OpenCL benchmarking tests
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	157	│ │ ├── GLES_COMPUTE --> GLES benchmarking tests
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	158	│ │ └── NEON --> NEON benchmarking tests
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	159	│ ├── datasets
				160	│ │ └── Datasets for all the validation / benchmark tests, layer configurations for various networks, etc.
				161	│ ├── framework
				162	│ │ └── Boiler plate code for both validation and benchmark test suites (Command line parsers, instruments, output loggers, etc.)
				163	│ ├── networks
				164	│ │ └── Examples of how to instantiate networks.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	165	│ ├── validation --> Sources for validation
				166	│ │ ├── Validation specific files
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	167	│ │ ├── CL --> OpenCL validation tests
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	168	│ │ ├── GLES_COMPUTE --> GLES validation tests
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	169	│ │ ├── CPP --> C++ reference implementations
				170	│ │ ├── fixtures
				171	│ │ │ └── Fixtures to initialise and run the runtime Functions.
				172	│ │ └── NEON --> NEON validation tests
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	173	│ └── dataset --> Datasets defining common sets of input parameters
				174	└── utils --> Boiler plate code used by examples
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	175	└── Various utilities to print types, load / store assets, etc.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	176
				177	@section S2_versions_changelog Release versions and changelog
				178
				179	@subsection S2_1_versions Release versions
				180
				181	All releases are numbered vYY.MM Where YY are the last two digits of the year, and MM the month number.
				182	If there is more than one release in a month then an extra sequential number is appended at the end:
				183
				184	v17.03 (First release of March 2017)
				185	v17.03.1 (Second release of March 2017)
				186	v17.04 (First release of April 2017)
				187
				188	@note We're aiming at releasing one major public release with new features per quarter. All releases in between will only contain bug fixes.
				189
				190	@subsection S2_2_changelog Changelog
				191
Anthony Barbier	2d0ce77	2018-02-21 15:35:36 +0000	[diff] [blame]	192	v18.02 Public major release
				193	- Various NEON / OpenCL / GLES optimisations.
				194	- Various bug fixes.
				195	- Changed default number of threads on big LITTLE systems.
				196	- Refactored examples and added:
				197	- graph_mobilenet_qassym8
				198	- graph_resnet
				199	- graph_squeezenet_v1_1
				200	- Renamed @ref arm_compute::CLConvolutionLayer into @ref arm_compute::CLGEMMConvolutionLayer and created a new @ref arm_compute::CLConvolutionLayer to select the fastest convolution method.
				201	- Renamed @ref arm_compute::NEConvolutionLayer into @ref arm_compute::NEGEMMConvolutionLayer and created a new @ref arm_compute::NEConvolutionLayer to select the fastest convolution method.
				202	- Added in place support to:
				203	- @ref arm_compute::CLActivationLayer
				204	- @ref arm_compute::CLBatchNormalizationLayer
				205	- Added QASYMM8 support to:
				206	- @ref arm_compute::CLActivationLayer
				207	- @ref arm_compute::CLDepthwiseConvolutionLayer
				208	- @ref arm_compute::NEDepthwiseConvolutionLayer
				209	- @ref arm_compute::NESoftmaxLayer
				210	- Added FP16 support to:
				211	- @ref arm_compute::CLDepthwiseConvolutionLayer3x3
				212	- @ref arm_compute::CLDepthwiseConvolutionLayer
				213	- Added broadcasting support to @ref arm_compute::NEArithmeticAddition / @ref arm_compute::CLArithmeticAddition / @ref arm_compute::CLPixelWiseMultiplication
				214	- Added fused batched normalization and activation to @ref arm_compute::CLBatchNormalizationLayer and @ref arm_compute::NEBatchNormalizationLayer
				215	- Added support for non-square pooling to @ref arm_compute::NEPoolingLayer and @ref arm_compute::CLPoolingLayer
				216	- New OpenCL kernels / functions:
				217	- @ref arm_compute::CLDirectConvolutionLayerOutputStageKernel
Pablo Tello	f6c572c	2018-02-14 12:47:30 +0000	[diff] [blame]	218	- New NEON kernels / functions
Anthony Barbier	2d0ce77	2018-02-21 15:35:36 +0000	[diff] [blame]	219	- Added name() method to all kernels.
				220	- Added support for Winograd 5x5.
				221	- @ref arm_compute::NEPermuteKernel / @ref arm_compute::NEPermute
Pablo Tello	f6c572c	2018-02-14 12:47:30 +0000	[diff] [blame]	222	- @ref arm_compute::NEWinogradLayerTransformInputKernel / @ref arm_compute::NEWinogradLayer
				223	- @ref arm_compute::NEWinogradLayerTransformOutputKernel / @ref arm_compute::NEWinogradLayer
				224	- @ref arm_compute::NEWinogradLayerTransformWeightsKernel / @ref arm_compute::NEWinogradLayer
				225	- Renamed arm_compute::NEWinogradLayerKernel into @ref arm_compute::NEWinogradLayerBatchedGEMMKernel
Anthony Barbier	2d0ce77	2018-02-21 15:35:36 +0000	[diff] [blame]	226	- New GLES kernels / functions:
				227	- @ref arm_compute::GCTensorShiftKernel / @ref arm_compute::GCTensorShift
Pablo Tello	f6c572c	2018-02-14 12:47:30 +0000	[diff] [blame]	228
Anthony Barbier	64c95a0	2018-01-22 18:48:55 +0000	[diff] [blame]	229	v18.01 Public maintenance release
				230	- Various bug fixes
				231	- Added some of the missing validate() methods
				232	- Added @ref arm_compute::CLDeconvolutionLayerUpsampleKernel / @ref arm_compute::CLDeconvolutionLayer @ref arm_compute::CLDeconvolutionLayerUpsample
				233	- Added @ref arm_compute::CLPermuteKernel / @ref arm_compute::CLPermute
				234	- Added method to clean the programs cache in the CL Kernel library.
				235	- Added @ref arm_compute::GCArithmeticAdditionKernel / @ref arm_compute::GCArithmeticAddition
				236	- Added @ref arm_compute::GCDepthwiseConvolutionLayer3x3Kernel / @ref arm_compute::GCDepthwiseConvolutionLayer3x3
				237	- Added @ref arm_compute::GCNormalizePlanarYUVLayerKernel / @ref arm_compute::GCNormalizePlanarYUVLayer
				238	- Added @ref arm_compute::GCScaleKernel / @ref arm_compute::GCScale
				239	- Added @ref arm_compute::GCWeightsReshapeKernel / @ref arm_compute::GCConvolutionLayer
				240	- Added FP16 support to the following GLES compute kernels:
				241	- @ref arm_compute::GCCol2ImKernel
				242	- @ref arm_compute::GCGEMMInterleave4x4Kernel
				243	- @ref arm_compute::GCGEMMTranspose1xWKernel
				244	- @ref arm_compute::GCIm2ColKernel
Pablo Tello	f6c572c	2018-02-14 12:47:30 +0000	[diff] [blame]	245	- Refactored NEON Winograd (arm_compute::NEWinogradLayerKernel)
Anthony Barbier	64c95a0	2018-01-22 18:48:55 +0000	[diff] [blame]	246	- Added @ref arm_compute::NEDirectConvolutionLayerOutputStageKernel
				247	- Added QASYMM8 support to the following NEON kernels:
				248	- @ref arm_compute::NEDepthwiseConvolutionLayer3x3Kernel
				249	- @ref arm_compute::NEFillBorderKernel
				250	- @ref arm_compute::NEPoolingLayerKernel
				251	- Added new examples:
				252	- graph_cl_mobilenet_qasymm8.cpp
				253	- graph_inception_v3.cpp
				254	- gc_dc.cpp
				255	- More tests added to both validation and benchmarking suites.
				256
Gian Marco	ff85093	2017-12-11 12:37:17 +0000	[diff] [blame]	257	v17.12 Public major release
				258	- Most machine learning functions on OpenCL support the new data type QASYMM8
				259	- Introduced logging interface
				260	- Introduced opencl timer
				261	- Reworked GEMMLowp interface
				262	- Added new NEON assembly kernels for GEMMLowp, SGEMM and HGEMM
				263	- Added validation method for most Machine Learning kernels / functions
				264	- Added new graph examples such as googlenet, mobilenet, squeezenet, vgg16 and vgg19
				265	- Added sgemm example for OpenCL
				266	- Added absolute difference example for GLES compute
				267	- Added new tests and benchmarks in validation and benchmark frameworks
				268	- Added new kernels / functions for GLES compute
				269
				270	- New OpenGL ES kernels / functions
				271	- @ref arm_compute::GCAbsoluteDifferenceKernel / @ref arm_compute::GCAbsoluteDifference
				272	- @ref arm_compute::GCActivationLayerKernel / @ref arm_compute::GCActivationLayer
				273	- @ref arm_compute::GCBatchNormalizationLayerKernel / @ref arm_compute::GCBatchNormalizationLayer
				274	- @ref arm_compute::GCCol2ImKernel
				275	- @ref arm_compute::GCDepthConcatenateLayerKernel / @ref arm_compute::GCDepthConcatenateLayer
				276	- @ref arm_compute::GCDirectConvolutionLayerKernel / @ref arm_compute::GCDirectConvolutionLayer
				277	- @ref arm_compute::GCDropoutLayerKernel / @ref arm_compute::GCDropoutLayer
				278	- @ref arm_compute::GCFillBorderKernel / @ref arm_compute::GCFillBorder
				279	- @ref arm_compute::GCGEMMInterleave4x4Kernel / @ref arm_compute::GCGEMMInterleave4x4
				280	- @ref arm_compute::GCGEMMMatrixAccumulateBiasesKernel / @ref arm_compute::GCGEMMMatrixAdditionKernel / @ref arm_compute::GCGEMMMatrixMultiplyKernel / @ref arm_compute::GCGEMM
				281	- @ref arm_compute::GCGEMMTranspose1xWKernel / @ref arm_compute::GCGEMMTranspose1xW
				282	- @ref arm_compute::GCIm2ColKernel
				283	- @ref arm_compute::GCNormalizationLayerKernel / @ref arm_compute::GCNormalizationLayer
				284	- @ref arm_compute::GCPixelWiseMultiplicationKernel / @ref arm_compute::GCPixelWiseMultiplication
				285	- @ref arm_compute::GCPoolingLayerKernel / @ref arm_compute::GCPoolingLayer
				286	- @ref arm_compute::GCLogits1DMaxKernel / @ref arm_compute::GCLogits1DShiftExpSumKernel / @ref arm_compute::GCLogits1DNormKernel / @ref arm_compute::GCSoftmaxLayer
				287	- @ref arm_compute::GCTransposeKernel / @ref arm_compute::GCTranspose
				288
				289	- New NEON kernels / functions
				290	- @ref arm_compute::NEGEMMLowpAArch64A53Kernel / @ref arm_compute::NEGEMMLowpAArch64Kernel / @ref arm_compute::NEGEMMLowpAArch64V8P4Kernel / arm_compute::NEGEMMInterleavedBlockedKernel / @ref arm_compute::NEGEMMLowpAssemblyMatrixMultiplyCore
				291	- @ref arm_compute::NEHGEMMAArch64FP16Kernel
				292	- @ref arm_compute::NEDepthwiseConvolutionLayer3x3Kernel / @ref arm_compute::NEDepthwiseIm2ColKernel / @ref arm_compute::NEGEMMMatrixVectorMultiplyKernel / @ref arm_compute::NEDepthwiseVectorToTensorKernel / @ref arm_compute::NEDepthwiseConvolutionLayer
				293	- @ref arm_compute::NEGEMMLowpOffsetContributionKernel / @ref arm_compute::NEGEMMLowpMatrixAReductionKernel / @ref arm_compute::NEGEMMLowpMatrixBReductionKernel / @ref arm_compute::NEGEMMLowpMatrixMultiplyCore
				294	- @ref arm_compute::NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel / @ref arm_compute::NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
				295	- @ref arm_compute::NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel / @ref arm_compute::NEGEMMLowpQuantizeDownInt32ToUint8Scale
Pablo Tello	f6c572c	2018-02-14 12:47:30 +0000	[diff] [blame]	296	- @ref arm_compute::NEWinogradLayer / arm_compute::NEWinogradLayerKernel
Gian Marco	ff85093	2017-12-11 12:37:17 +0000	[diff] [blame]	297
				298	- New OpenCL kernels / functions
				299	- @ref arm_compute::CLGEMMLowpOffsetContributionKernel / @ref arm_compute::CLGEMMLowpMatrixAReductionKernel / @ref arm_compute::CLGEMMLowpMatrixBReductionKernel / @ref arm_compute::CLGEMMLowpMatrixMultiplyCore
				300	- @ref arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel / @ref arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint
				301	- @ref arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel / @ref arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8Scale
				302
				303	- New graph nodes for NEON and OpenCL
				304	- @ref arm_compute::graph::BranchLayer
				305	- @ref arm_compute::graph::DepthConvertLayer
				306	- @ref arm_compute::graph::DepthwiseConvolutionLayer
				307	- @ref arm_compute::graph::DequantizationLayer
				308	- @ref arm_compute::graph::FlattenLayer
				309	- @ref arm_compute::graph::QuantizationLayer
				310	- @ref arm_compute::graph::ReshapeLayer
				311
Anthony Barbier	3c5b4ff	2017-10-12 13:20:52 +0100	[diff] [blame]	312	v17.10 Public maintenance release
				313	- Bug fixes:
				314	- Check the maximum local workgroup size supported by OpenCL devices
				315	- Minor documentation updates (Fixed instructions to build the examples)
				316	- Introduced a arm_compute::graph::GraphContext
				317	- Added a few new Graph nodes, support for branches and grouping.
				318	- Automatically enable cl_printf in debug builds
				319	- Fixed bare metal builds for armv7a
				320	- Added AlexNet and cartoon effect examples
				321	- Fixed library builds: libraries are no longer built as supersets of each other.(It means application using the Runtime part of the library now need to link against both libarm_compute_core and libarm_compute)
				322
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	323	v17.09 Public major release
				324	- Experimental Graph support: initial implementation of a simple stream API to easily chain machine learning layers.
				325	- Memory Manager (@ref arm_compute::BlobLifetimeManager, @ref arm_compute::BlobMemoryPool, @ref arm_compute::ILifetimeManager, @ref arm_compute::IMemoryGroup, @ref arm_compute::IMemoryManager, @ref arm_compute::IMemoryPool, @ref arm_compute::IPoolManager, @ref arm_compute::MemoryManagerOnDemand, @ref arm_compute::PoolManager)
				326	- New validation and benchmark frameworks (Boost and Google frameworks replaced by homemade framework).
				327	- Most machine learning functions support both fixed point 8 and 16 bit (QS8, QS16) for both NEON and OpenCL.
				328	- New NEON kernels / functions:
				329	- @ref arm_compute::NEGEMMAssemblyBaseKernel @ref arm_compute::NEGEMMAArch64Kernel
				330	- @ref arm_compute::NEDequantizationLayerKernel / @ref arm_compute::NEDequantizationLayer
				331	- @ref arm_compute::NEFloorKernel / @ref arm_compute::NEFloor
Giorgio Arena	04a8f8c	2017-11-23 11:45:24 +0000	[diff] [blame]	332	- @ref arm_compute::NEL2NormalizeLayerKernel / @ref arm_compute::NEL2NormalizeLayer
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	333	- @ref arm_compute::NEQuantizationLayerKernel @ref arm_compute::NEMinMaxLayerKernel / @ref arm_compute::NEQuantizationLayer
				334	- @ref arm_compute::NEROIPoolingLayerKernel / @ref arm_compute::NEROIPoolingLayer
				335	- @ref arm_compute::NEReductionOperationKernel / @ref arm_compute::NEReductionOperation
				336	- @ref arm_compute::NEReshapeLayerKernel / @ref arm_compute::NEReshapeLayer
				337
				338	- New OpenCL kernels / functions:
Giorgio Arena	04a8f8c	2017-11-23 11:45:24 +0000	[diff] [blame]	339	- @ref arm_compute::CLDepthwiseConvolutionLayer3x3Kernel @ref arm_compute::CLDepthwiseIm2ColKernel @ref arm_compute::CLDepthwiseVectorToTensorKernel @ref arm_compute::CLDepthwiseWeightsReshapeKernel / @ref arm_compute::CLDepthwiseConvolutionLayer3x3 @ref arm_compute::CLDepthwiseConvolutionLayer @ref arm_compute::CLDepthwiseSeparableConvolutionLayer
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	340	- @ref arm_compute::CLDequantizationLayerKernel / @ref arm_compute::CLDequantizationLayer
				341	- @ref arm_compute::CLDirectConvolutionLayerKernel / @ref arm_compute::CLDirectConvolutionLayer
				342	- @ref arm_compute::CLFlattenLayer
				343	- @ref arm_compute::CLFloorKernel / @ref arm_compute::CLFloor
				344	- @ref arm_compute::CLGEMMTranspose1xW
				345	- @ref arm_compute::CLGEMMMatrixVectorMultiplyKernel
Giorgio Arena	04a8f8c	2017-11-23 11:45:24 +0000	[diff] [blame]	346	- @ref arm_compute::CLL2NormalizeLayerKernel / @ref arm_compute::CLL2NormalizeLayer
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	347	- @ref arm_compute::CLQuantizationLayerKernel @ref arm_compute::CLMinMaxLayerKernel / @ref arm_compute::CLQuantizationLayer
				348	- @ref arm_compute::CLROIPoolingLayerKernel / @ref arm_compute::CLROIPoolingLayer
				349	- @ref arm_compute::CLReductionOperationKernel / @ref arm_compute::CLReductionOperation
				350	- @ref arm_compute::CLReshapeLayerKernel / @ref arm_compute::CLReshapeLayer
				351
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	352	v17.06 Public major release
				353	- Various bug fixes
				354	- Added support for fixed point 8 bit (QS8) to the various NEON machine learning kernels.
				355	- Added unit tests and benchmarks (AlexNet, LeNet)
				356	- Added support for sub tensors.
				357	- Added infrastructure to provide GPU specific optimisation for some OpenCL kernels.
				358	- Added @ref arm_compute::OMPScheduler (OpenMP) scheduler for NEON
				359	- Added @ref arm_compute::SingleThreadScheduler scheduler for NEON (For bare metal)
				360	- User can specify his own scheduler by implementing the @ref arm_compute::IScheduler interface.
				361	- New OpenCL kernels / functions:
				362	- @ref arm_compute::CLBatchNormalizationLayerKernel / @ref arm_compute::CLBatchNormalizationLayer
Giorgio Arena	04a8f8c	2017-11-23 11:45:24 +0000	[diff] [blame]	363	- @ref arm_compute::CLDepthConcatenateLayerKernel / @ref arm_compute::CLDepthConcatenateLayer
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	364	- @ref arm_compute::CLHOGOrientationBinningKernel @ref arm_compute::CLHOGBlockNormalizationKernel, @ref arm_compute::CLHOGDetectorKernel / @ref arm_compute::CLHOGDescriptor @ref arm_compute::CLHOGDetector @ref arm_compute::CLHOGGradient @ref arm_compute::CLHOGMultiDetection
				365	- @ref arm_compute::CLLocallyConnectedMatrixMultiplyKernel / @ref arm_compute::CLLocallyConnectedLayer
				366	- @ref arm_compute::CLWeightsReshapeKernel / @ref arm_compute::CLConvolutionLayerReshapeWeights
				367	- New C++ kernels:
				368	- @ref arm_compute::CPPDetectionWindowNonMaximaSuppressionKernel
				369	- New NEON kernels / functions:
				370	- @ref arm_compute::NEBatchNormalizationLayerKernel / @ref arm_compute::NEBatchNormalizationLayer
Giorgio Arena	04a8f8c	2017-11-23 11:45:24 +0000	[diff] [blame]	371	- @ref arm_compute::NEDepthConcatenateLayerKernel / @ref arm_compute::NEDepthConcatenateLayer
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	372	- @ref arm_compute::NEDirectConvolutionLayerKernel / @ref arm_compute::NEDirectConvolutionLayer
				373	- @ref arm_compute::NELocallyConnectedMatrixMultiplyKernel / @ref arm_compute::NELocallyConnectedLayer
				374	- @ref arm_compute::NEWeightsReshapeKernel / @ref arm_compute::NEConvolutionLayerReshapeWeights
				375
				376	v17.05 Public bug fixes release
				377	- Various bug fixes
				378	- Remaining of the functions ported to use accurate padding.
				379	- Library does not link against OpenCL anymore (It uses dlopen / dlsym at runtime instead to determine whether or not OpenCL is available).
				380	- Added "free" method to allocator.
				381	- Minimum version of g++ required for armv7 Linux changed from 4.8 to 4.9
				382
				383	v17.04 Public bug fixes release
				384
				385	The following functions have been ported to use the new accurate padding:
				386	- @ref arm_compute::CLColorConvertKernel
				387	- @ref arm_compute::CLEdgeNonMaxSuppressionKernel
				388	- @ref arm_compute::CLEdgeTraceKernel
				389	- @ref arm_compute::CLGaussianPyramidHorKernel
				390	- @ref arm_compute::CLGaussianPyramidVertKernel
				391	- @ref arm_compute::CLGradientKernel
				392	- @ref arm_compute::NEChannelCombineKernel
				393	- @ref arm_compute::NEFillArrayKernel
				394	- @ref arm_compute::NEGaussianPyramidHorKernel
				395	- @ref arm_compute::NEGaussianPyramidVertKernel
				396	- @ref arm_compute::NEHarrisScoreFP16Kernel
				397	- @ref arm_compute::NEHarrisScoreKernel
				398	- @ref arm_compute::NEHOGDetectorKernel
				399	- @ref arm_compute::NELogits1DMaxKernel
Diego Lopez Recas	35ceeb2	2017-12-04 18:56:10 +0000	[diff] [blame]	400	- arm_compute::NELogits1DShiftExpSumKernel
				401	- arm_compute::NELogits1DNormKernel
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	402	- @ref arm_compute::NENonMaximaSuppression3x3FP16Kernel
				403	- @ref arm_compute::NENonMaximaSuppression3x3Kernel
				404
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	405	v17.03.1 First Major public release of the sources
				406	- Renamed the library to arm_compute
				407	- New CPP target introduced for C++ kernels shared between NEON and CL functions.
				408	- New padding calculation interface introduced and ported most kernels / functions to use it.
				409	- New OpenCL kernels / functions:
Gian Marco	05288a2	2017-11-21 10:57:50 +0000	[diff] [blame]	410	- @ref arm_compute::CLGEMMLowpMatrixMultiplyKernel / arm_compute::CLGEMMLowp
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	411	- New NEON kernels / functions:
				412	- @ref arm_compute::NENormalizationLayerKernel / @ref arm_compute::NENormalizationLayer
				413	- @ref arm_compute::NETransposeKernel / @ref arm_compute::NETranspose
Diego Lopez Recas	35ceeb2	2017-12-04 18:56:10 +0000	[diff] [blame]	414	- @ref arm_compute::NELogits1DMaxKernel, arm_compute::NELogits1DShiftExpSumKernel, arm_compute::NELogits1DNormKernel / @ref arm_compute::NESoftmaxLayer
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	415	- @ref arm_compute::NEIm2ColKernel, @ref arm_compute::NECol2ImKernel, arm_compute::NEConvolutionLayerWeightsReshapeKernel / @ref arm_compute::NEConvolutionLayer
				416	- @ref arm_compute::NEGEMMMatrixAccumulateBiasesKernel / @ref arm_compute::NEFullyConnectedLayer
Gian Marco	e75a02b	2017-11-08 12:24:09 +0000	[diff] [blame]	417	- @ref arm_compute::NEGEMMLowpMatrixMultiplyKernel / arm_compute::NEGEMMLowp
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	418
				419	v17.03 Sources preview
				420	- New OpenCL kernels / functions:
				421	- @ref arm_compute::CLGradientKernel, @ref arm_compute::CLEdgeNonMaxSuppressionKernel, @ref arm_compute::CLEdgeTraceKernel / @ref arm_compute::CLCannyEdge
				422	- GEMM refactoring + FP16 support: @ref arm_compute::CLGEMMInterleave4x4Kernel, @ref arm_compute::CLGEMMTranspose1xWKernel, @ref arm_compute::CLGEMMMatrixMultiplyKernel, @ref arm_compute::CLGEMMMatrixAdditionKernel / @ref arm_compute::CLGEMM
				423	- @ref arm_compute::CLGEMMMatrixAccumulateBiasesKernel / @ref arm_compute::CLFullyConnectedLayer
				424	- @ref arm_compute::CLTransposeKernel / @ref arm_compute::CLTranspose
				425	- @ref arm_compute::CLLKTrackerInitKernel, @ref arm_compute::CLLKTrackerStage0Kernel, @ref arm_compute::CLLKTrackerStage1Kernel, @ref arm_compute::CLLKTrackerFinalizeKernel / @ref arm_compute::CLOpticalFlow
				426	- @ref arm_compute::CLNormalizationLayerKernel / @ref arm_compute::CLNormalizationLayer
				427	- @ref arm_compute::CLLaplacianPyramid, @ref arm_compute::CLLaplacianReconstruct
				428	- New NEON kernels / functions:
				429	- @ref arm_compute::NEActivationLayerKernel / @ref arm_compute::NEActivationLayer
				430	- GEMM refactoring + FP16 support (Requires armv8.2 CPU): @ref arm_compute::NEGEMMInterleave4x4Kernel, @ref arm_compute::NEGEMMTranspose1xWKernel, @ref arm_compute::NEGEMMMatrixMultiplyKernel, @ref arm_compute::NEGEMMMatrixAdditionKernel / @ref arm_compute::NEGEMM
				431	- @ref arm_compute::NEPoolingLayerKernel / @ref arm_compute::NEPoolingLayer
				432
				433	v17.02.1 Sources preview
				434	- New OpenCL kernels / functions:
				435	- @ref arm_compute::CLLogits1DMaxKernel, @ref arm_compute::CLLogits1DShiftExpSumKernel, @ref arm_compute::CLLogits1DNormKernel / @ref arm_compute::CLSoftmaxLayer
				436	- @ref arm_compute::CLPoolingLayerKernel / @ref arm_compute::CLPoolingLayer
Gian Marco Iodice	5cb4c42	2017-06-23 10:38:25 +0100	[diff] [blame]	437	- @ref arm_compute::CLIm2ColKernel, @ref arm_compute::CLCol2ImKernel, arm_compute::CLConvolutionLayerWeightsReshapeKernel / @ref arm_compute::CLConvolutionLayer
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	438	- @ref arm_compute::CLRemapKernel / @ref arm_compute::CLRemap
				439	- @ref arm_compute::CLGaussianPyramidHorKernel, @ref arm_compute::CLGaussianPyramidVertKernel / @ref arm_compute::CLGaussianPyramid, @ref arm_compute::CLGaussianPyramidHalf, @ref arm_compute::CLGaussianPyramidOrb
				440	- @ref arm_compute::CLMinMaxKernel, @ref arm_compute::CLMinMaxLocationKernel / @ref arm_compute::CLMinMaxLocation
				441	- @ref arm_compute::CLNonLinearFilterKernel / @ref arm_compute::CLNonLinearFilter
				442	- New NEON FP16 kernels (Requires armv8.2 CPU)
				443	- @ref arm_compute::NEAccumulateWeightedFP16Kernel
				444	- @ref arm_compute::NEBox3x3FP16Kernel
				445	- @ref arm_compute::NENonMaximaSuppression3x3FP16Kernel
				446
				447	v17.02 Sources preview
				448	- New OpenCL kernels / functions:
				449	- @ref arm_compute::CLActivationLayerKernel / @ref arm_compute::CLActivationLayer
				450	- @ref arm_compute::CLChannelCombineKernel / @ref arm_compute::CLChannelCombine
				451	- @ref arm_compute::CLDerivativeKernel / @ref arm_compute::CLChannelExtract
				452	- @ref arm_compute::CLFastCornersKernel / @ref arm_compute::CLFastCorners
				453	- @ref arm_compute::CLMeanStdDevKernel / @ref arm_compute::CLMeanStdDev
				454	- New NEON kernels / functions:
				455	- HOG / SVM: @ref arm_compute::NEHOGOrientationBinningKernel, @ref arm_compute::NEHOGBlockNormalizationKernel, @ref arm_compute::NEHOGDetectorKernel, arm_compute::NEHOGNonMaximaSuppressionKernel / @ref arm_compute::NEHOGDescriptor, @ref arm_compute::NEHOGDetector, @ref arm_compute::NEHOGGradient, @ref arm_compute::NEHOGMultiDetection
				456	- @ref arm_compute::NENonLinearFilterKernel / @ref arm_compute::NENonLinearFilter
				457	- Introduced a CLScheduler to manage the default context and command queue used by the runtime library and create synchronisation events.
				458	- Switched all the kernels / functions to use tensors instead of images.
				459	- Updated documentation to include instructions to build the library from sources.
				460
				461	v16.12 Binary preview release
				462	- Original release
				463
				464	@section S3_how_to_build How to build the library and the examples
				465
				466	@subsection S3_1_build_options Build options
				467
				468	scons 2.3 or above is required to build the library.
				469	To see the build options available simply run ```scons -h```:
				470
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	471	debug: Debug (yes\|no)
				472	default: False
				473	actual: False
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	474
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	475	asserts: Enable asserts (this flag is forced to 1 for debug=1) (yes\|no)
				476	default: False
				477	actual: False
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	478
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	479	arch: Target Architecture (armv7a\|arm64-v8a\|arm64-v8.2-a\|x86_32\|x86_64)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	480	default: armv7a
				481	actual: armv7a
				482
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	483	os: Target OS (linux\|android\|bare_metal)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	484	default: linux
				485	actual: linux
				486
Anthony Barbier	2d0ce77	2018-02-21 15:35:36 +0000	[diff] [blame]	487	build: Build type (native\|cross_compile\|embed_only)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	488	default: cross_compile
				489	actual: cross_compile
				490
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	491	examples: Build example programs (yes\|no)
				492	default: True
				493	actual: True
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	494
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	495	Werror: Enable/disable the -Werror compilation flag (yes\|no)
				496	default: True
				497	actual: True
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	498
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	499	opencl: Enable OpenCL support (yes\|no)
				500	default: True
				501	actual: True
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	502
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	503	neon: Enable Neon support (yes\|no)
				504	default: False
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	505	actual: False
				506
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	507	gles_compute: Enable OpenGL ES Compute Shader support (yes\|no)
				508	default: False
				509	actual: False
				510
				511	embed_kernels: Embed OpenCL kernels and OpenGL ES compute shader in library binary (yes\|no)
Anthony Barbier	cc0a80b	2017-12-15 11:37:29 +0000	[diff] [blame]	512	default: True
				513	actual: True
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	514
				515	set_soname: Set the library's soname and shlibversion (requires SCons 2.4 or above) (yes\|no)
				516	default: False
				517	actual: False
				518
				519	openmp: Enable OpenMP backend (yes\|no)
				520	default: False
				521	actual: False
				522
				523	cppthreads: Enable C++11 threads backend (yes\|no)
				524	default: True
				525	actual: True
				526
				527	build_dir: Specify sub-folder for the build ( /path/to/build_dir )
				528	default: .
				529	actual: .
				530
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	531	extra_cxx_flags: Extra CXX flags to be appended to the build command
				532	default:
				533	actual:
				534
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	535	pmu: Enable PMU counters (yes\|no)
				536	default: False
				537	actual: False
				538
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	539	mali: Enable Mali hardware counters (yes\|no)
				540	default: False
				541	actual: False
				542
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	543	validation_tests: Build validation test programs (yes\|no)
				544	default: False
				545	actual: False
				546
				547	benchmark_tests: Build benchmark test programs (yes\|no)
				548	default: False
				549	actual: False
				550
				551	@b debug / @b asserts:
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	552	- With debug=1 asserts are enabled, and the library is built with symbols and no optimisations enabled.
				553	- With debug=0 and asserts=1: Optimisations are enabled and symbols are removed, however all the asserts are still present (This is about 20% slower than the release build)
				554	- With debug=0 and asserts=0: All optimisations are enable and no validation is performed, if the application misuses the library it is likely to result in a crash. (Only use this mode once you are sure your application is working as expected).
				555
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	556	@b arch: The x86_32 and x86_64 targets can only be used with neon=0 and opencl=1.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	557
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	558	@b os: Choose the operating system you are targeting: Linux, Android or bare metal.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	559	@note bare metal can only be used for NEON (not OpenCL), only static libraries get built and NEON's multi-threading support is disabled.
				560
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	561	@b build: you can either build directly on your device (native) or cross compile from your desktop machine (cross-compile). In both cases make sure the compiler is available in your path.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	562
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	563	@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.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	564
Anthony Barbier	2d0ce77	2018-02-21 15:35:36 +0000	[diff] [blame]	565	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.
				566
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	567	@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).
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	568
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	569	@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)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	570
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	571	@b embed_kernels: For OpenCL / GLES_COMPUTE only: set embed_kernels=1 if you want the OpenCL / GLES_COMPUTE kernels to be built in the library's binaries instead of being read from separate ".cl" / ".cs" files. If embed_kernels is set to 0 then the application can set the path to the folder containing the OpenCL / GLES_COMPUTE kernel files by calling CLKernelLibrary::init() / GCKernelLibrary::init(). By default the path is set to "./cl_kernels" / "./cs_shaders".
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	572
				573	@b set_soname: Do you want to build the versioned version of the library ?
				574
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	575	If enabled the library will contain a SONAME and SHLIBVERSION and some symlinks will automatically be created between the objects.
				576	Example:
				577	libarm_compute_core.so -> libarm_compute_core.so.1.0.0
				578	libarm_compute_core.so.1 -> libarm_compute_core.so.1.0.0
				579	libarm_compute_core.so.1.0.0
				580
				581	@note This options is disabled by default as it requires SCons version 2.4 or above.
				582
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	583	@b extra_cxx_flags: Custom CXX flags which will be appended to the end of the build command.
				584
				585	@b build_dir: Build the library in a subfolder of the "build" folder. (Allows to build several configurations in parallel).
				586
				587	@b examples: Build or not the examples
				588
				589	@b validation_tests: Enable the build of the validation suite.
				590
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	591	@b benchmark_tests: Enable the build of the benchmark tests
				592
				593	@b pmu: Enable the PMU cycle counter to measure execution time in benchmark tests. (Your device needs to support it)
				594
Anthony Barbier	6a5627a	2017-09-26 14:42:02 +0100	[diff] [blame]	595	@b mali: Enable the collection of Mali hardware counters to measure execution time in benchmark tests. (Your device needs to have a Mali driver that supports it)
				596
Anthony Barbier	79c6178	2017-06-23 11:48:24 +0100	[diff] [blame]	597	@b openmp Build in the OpenMP scheduler for NEON.
				598
				599	@note Only works when building with g++ not clang++
				600
				601	@b cppthreads Build in the C++11 scheduler for NEON.
				602
				603	@sa arm_compute::Scheduler::set
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	604
Moritz Pflanzer	07674de	2017-07-21 09:39:36 +0100	[diff] [blame]	605	@subsection S3_2_linux Building for Linux
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	606
				607	@subsubsection S3_2_1_library How to build the library ?
				608
				609	For Linux, the library was successfully built and tested using the following Linaro GCC toolchain:
				610
				611	- gcc-linaro-arm-linux-gnueabihf-4.9-2014.07_linux
				612	- gcc-linaro-4.9-2016.02-x86_64_aarch64-linux-gnu
				613	- gcc-linaro-6.3.1-2017.02-i686_aarch64-linux-gnu
				614
				615	@note If you are building with opencl=1 then scons will expect to find libOpenCL.so either in the current directory or in "build" (See the section below if you need a stub OpenCL library to link against)
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	616	@note If you are building with gles_compute=1 then scons will expect to find libEGL.so / libGLESv1_CM.so / libGLESv2.so either in the current directory or in "build" (See the section below if you need a stub OpenCL library to link against)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	617
				618	To cross-compile the library in debug mode, with NEON only support, for Linux 32bit:
				619
				620	scons Werror=1 -j8 debug=1 neon=1 opencl=0 os=linux arch=armv7a
				621
				622	To cross-compile the library in asserts mode, with OpenCL only support, for Linux 64bit:
				623
				624	scons Werror=1 -j8 debug=0 asserts=1 neon=0 opencl=1 embed_kernels=1 os=linux arch=arm64-v8a
				625
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	626	To cross-compile the library in asserts mode, with GLES_COMPUTE only support, for Linux 64bit:
				627
				628	scons Werror=1 -j8 debug=0 asserts=1 neon=0 opencl=0 gles_compute=1 embed_kernels=1 os=linux arch=arm64-v8a
				629
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	630	You can also compile the library natively on an ARM device by using <b>build=native</b>:
				631
				632	scons Werror=1 -j8 debug=0 neon=1 opencl=0 os=linux arch=arm64-v8a build=native
				633	scons Werror=1 -j8 debug=0 neon=1 opencl=0 os=linux arch=armv7a build=native
				634
				635	@note g++ for ARM is mono-arch, therefore if you want to compile for Linux 32bit on a Linux 64bit platform you will have to use a cross compiler.
				636
				637	For example on a 64bit Debian based system you would have to install <b>g++-arm-linux-gnueabihf</b>
				638
				639	apt-get install g++-arm-linux-gnueabihf
				640
				641	Then run
				642
				643	scons Werror=1 -j8 debug=0 neon=1 opencl=0 os=linux arch=armv7a build=cross_compile
				644
				645	or simply remove the build parameter as build=cross_compile is the default value:
				646
				647	scons Werror=1 -j8 debug=0 neon=1 opencl=0 os=linux arch=armv7a
				648
				649	@attention To cross compile with opencl=1 you need to make sure to have a version of libOpenCL matching your target architecture.
				650
				651	@subsubsection S3_2_2_examples How to manually build the examples ?
				652
				653	The examples get automatically built by scons as part of the build process of the library described above. This section just describes how you can build and link your own application against our library.
				654
				655	@note The following command lines assume the arm_compute and libOpenCL binaries are present in the current directory or in the system library path. If this is not the case you can specify the location of the pre-built library with the compiler option -L. When building the OpenCL example the commands below assume that the CL headers are located in the include folder where the command is executed.
				656
				657	To cross compile a NEON example for Linux 32bit:
				658
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	659	arm-linux-gnueabihf-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute -larm_compute_core -o neon_convolution
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	660
				661	To cross compile a NEON example for Linux 64bit:
				662
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	663	aarch64-linux-gnu-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute -larm_compute_core -o neon_convolution
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	664
				665	(notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different)
				666
				667	To cross compile an OpenCL example for Linux 32bit:
				668
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	669	arm-linux-gnueabihf-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute -larm_compute_core -lOpenCL -o cl_convolution -DARM_COMPUTE_CL
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	670
				671	To cross compile an OpenCL example for Linux 64bit:
				672
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	673	aarch64-linux-gnu-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute -larm_compute_core -lOpenCL -o cl_convolution -DARM_COMPUTE_CL
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	674
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	675	To cross compile a GLES example for Linux 32bit:
				676
				677	arm-linux-gnueabihf-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -mfpu=neon -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff
				678
				679	To cross compile a GLES example for Linux 64bit:
				680
				681	aarch64-linux-gnu-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff
				682
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	683	(notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different)
				684
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	685	To cross compile the examples with the Graph API, such as graph_lenet.cpp, you need to link the examples against arm_compute_graph.so too.
				686
				687	@note The compute library must currently be built with both neon and opencl enabled - neon=1 and opencl=1
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	688
				689	i.e. to cross compile the "graph_lenet" example for Linux 32bit:
				690
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	691	arm-linux-gnueabihf-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	692
				693	i.e. to cross compile the "graph_lenet" example for Linux 64bit:
				694
Isabella Gottardi	b28f29d	2017-11-09 17:05:07 +0000	[diff] [blame]	695	aarch64-linux-gnu-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	696
				697	(notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different)
				698
Anthony Barbier	e500747	2017-10-27 15:01:44 +0100	[diff] [blame]	699	@note If compiling using static libraries, this order must be followed when linking: arm_compute_graph_static, arm_compute, arm_compute_core
				700
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	701	To compile natively (i.e directly on an ARM device) for NEON for Linux 32bit:
				702
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	703	g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -larm_compute -larm_compute_core -o neon_convolution
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	704
				705	To compile natively (i.e directly on an ARM device) for NEON for Linux 64bit:
				706
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	707	g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute -larm_compute_core -o neon_convolution
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	708
				709	(notice the only difference with the 32 bit command is that we don't need the -mfpu option)
				710
				711	To compile natively (i.e directly on an ARM device) for OpenCL for Linux 32bit or Linux 64bit:
				712
Anthony Barbier	b2881fc	2017-09-29 17:12:12 +0100	[diff] [blame]	713	g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute -larm_compute_core -lOpenCL -o cl_convolution -DARM_COMPUTE_CL
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	714
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	715	To compile natively (i.e directly on an ARM device) for GLES for Linux 32bit or Linux 64bit:
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	716
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	717	g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff
				718
				719	To compile natively the examples with the Graph API, such as graph_lenet.cpp, you need to link the examples against arm_compute_graph.so too.
				720	@note The compute library must currently be built with both neon and opencl enabled - neon=1 and opencl=1
				721
				722	i.e. to natively compile the "graph_lenet" example for Linux 32bit:
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	723
Isabella Gottardi	b28f29d	2017-11-09 17:05:07 +0000	[diff] [blame]	724	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	725
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	726	i.e. to natively compile the "graph_lenet" example for Linux 64bit:
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	727
Isabella Gottardi	b28f29d	2017-11-09 17:05:07 +0000	[diff] [blame]	728	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	729
				730	(notice the only difference with the 32 bit command is that we don't need the -mfpu option)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	731
Anthony Barbier	e500747	2017-10-27 15:01:44 +0100	[diff] [blame]	732	@note If compiling using static libraries, this order must be followed when linking: arm_compute_graph_static, arm_compute, arm_compute_core
				733
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	734	@note These two commands assume libarm_compute.so is available in your library path, if not add the path to it using -L
				735
				736	To run the built executable simply run:
				737
				738	LD_LIBRARY_PATH=build ./neon_convolution
				739
				740	or
				741
				742	LD_LIBRARY_PATH=build ./cl_convolution
				743
Moritz Pflanzer	07674de	2017-07-21 09:39:36 +0100	[diff] [blame]	744	@subsection S3_3_android Building for Android
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	745
				746	For Android, the library was successfully built and tested using Google's standalone toolchains:
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	747	- NDK r14 arm-linux-androideabi-4.9 for armv7a (clang++)
				748	- NDK r14 aarch64-linux-android-4.9 for arm64-v8a (clang++)
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	749
				750	Here is a guide to <a href="https://developer.android.com/ndk/guides/standalone_toolchain.html">create your Android standalone toolchains from the NDK</a>
				751
				752	- Download the NDK r14 from here: https://developer.android.com/ndk/downloads/index.html
				753	- Make sure you have Python 2 installed on your machine.
				754	- Generate the 32 and/or 64 toolchains by running the following commands:
				755
				756
Anthony Barbier	e500747	2017-10-27 15:01:44 +0100	[diff] [blame]	757	$NDK/build/tools/make_standalone_toolchain.py --arch arm64 --install-dir $MY_TOOLCHAINS/aarch64-linux-android-4.9 --stl gnustl --api 21
				758	$NDK/build/tools/make_standalone_toolchain.py --arch arm --install-dir $MY_TOOLCHAINS/arm-linux-androideabi-4.9 --stl gnustl --api 21
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	759
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	760	@attention Due to some NDK issues make sure you use clang++ & gnustl
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	761
				762	@note Make sure to add the toolchains to your PATH: export PATH=$PATH:$MY_TOOLCHAINS/aarch64-linux-android-4.9/bin:$MY_TOOLCHAINS/arm-linux-androideabi-4.9/bin
				763
				764	@subsubsection S3_3_1_library How to build the library ?
				765
				766	@note If you are building with opencl=1 then scons will expect to find libOpenCL.so either in the current directory or in "build" (See the section below if you need a stub OpenCL library to link against)
				767
				768	To cross-compile the library in debug mode, with NEON only support, for Android 32bit:
				769
				770	CXX=clang++ CC=clang scons Werror=1 -j8 debug=1 neon=1 opencl=0 os=android arch=armv7a
				771
				772	To cross-compile the library in asserts mode, with OpenCL only support, for Android 64bit:
				773
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	774	CXX=clang++ CC=clang scons Werror=1 -j8 debug=0 asserts=1 neon=0 opencl=1 embed_kernels=1 os=android arch=arm64-v8a
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	775
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	776	To cross-compile the library in asserts mode, with GLES_COMPUTE only support, for Android 64bit:
				777
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	778	CXX=clang++ CC=clang scons Werror=1 -j8 debug=0 asserts=1 neon=0 opencl=0 gles_compute=1 embed_kernels=1 os=android arch=arm64-v8a
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	779
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	780	@subsubsection S3_3_2_examples How to manually build the examples ?
				781
				782	The examples get automatically built by scons as part of the build process of the library described above. This section just describes how you can build and link your own application against our library.
				783
Anthony Barbier	fabb038	2017-06-23 14:42:52 +0100	[diff] [blame]	784	@note The following command lines assume the arm_compute and libOpenCL binaries are present in the current directory or in the system library path. If this is not the case you can specify the location of the pre-built library with the compiler option -L. When building the OpenCL example the commands below assume that the CL headers are located in the include folder where the command is executed.
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	785
				786	Once you've got your Android standalone toolchain built and added to your path you can do the following:
				787
				788	To cross compile a NEON example:
				789
				790	#32 bit:
Georgios Pinitas	9873ea3	2017-12-05 15:28:55 +0000	[diff] [blame]	791	arm-linux-androideabi-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_arm -static-libstdc++ -pie
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	792	#64 bit:
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	793	aarch64-linux-android-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_aarch64 -static-libstdc++ -pie
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	794
				795	To cross compile an OpenCL example:
				796
				797	#32 bit:
Georgios Pinitas	9873ea3	2017-12-05 15:28:55 +0000	[diff] [blame]	798	arm-linux-androideabi-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_arm -static-libstdc++ -pie -lOpenCL -DARM_COMPUTE_CL
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	799	#64 bit:
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	800	aarch64-linux-android-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_aarch64 -static-libstdc++ -pie -lOpenCL -DARM_COMPUTE_CL
				801
				802	To cross compile a GLES example:
Anthony Barbier	cc0a80b	2017-12-15 11:37:29 +0000	[diff] [blame]	803
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	804	#32 bit:
				805	arm-linux-androideabi-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_arm -static-libstdc++ -pie -DARM_COMPUTE_GC
				806	#64 bit:
				807	aarch64-linux-android-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_GC
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	808
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	809	To cross compile the examples with the Graph API, such as graph_lenet.cpp, you need to link the library arm_compute_graph also.
				810	(notice the compute library has to be built with both neon and opencl enabled - neon=1 and opencl=1)
				811
				812	#32 bit:
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	813	arm-linux-androideabi-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_arm -static-libstdc++ -pie -lOpenCL -DARM_COMPUTE_CL
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	814	#64 bit:
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	815	aarch64-linux-android-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_aarch64 -static-libstdc++ -pie -lOpenCL -DARM_COMPUTE_CL
Gian Marco Iodice	daec1aa	2017-09-29 12:03:18 +0100	[diff] [blame]	816
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	817	@note Due to some issues in older versions of the Mali OpenCL DDK (<= r13p0), we recommend to link arm_compute statically on Android.
Anthony Barbier	20dbb82	2017-12-13 21:19:39 +0000	[diff] [blame]	818	@note When linked statically the arm_compute_graph library currently needs the --whole-archive linker flag in order to work properly
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	819
				820	Then you need to do is upload the executable and the shared library to the device using ADB:
				821
				822	adb push neon_convolution_arm /data/local/tmp/
				823	adb push cl_convolution_arm /data/local/tmp/
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	824	adb push gc_absdiff_arm /data/local/tmp/
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	825	adb shell chmod 777 -R /data/local/tmp/
				826
				827	And finally to run the example:
				828
				829	adb shell /data/local/tmp/neon_convolution_arm
				830	adb shell /data/local/tmp/cl_convolution_arm
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	831	adb shell /data/local/tmp/gc_absdiff_arm
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	832
				833	For 64bit:
				834
				835	adb push neon_convolution_aarch64 /data/local/tmp/
				836	adb push cl_convolution_aarch64 /data/local/tmp/
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	837	adb push gc_absdiff_aarch64 /data/local/tmp/
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	838	adb shell chmod 777 -R /data/local/tmp/
				839
				840	And finally to run the example:
				841
				842	adb shell /data/local/tmp/neon_convolution_aarch64
				843	adb shell /data/local/tmp/cl_convolution_aarch64
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	844	adb shell /data/local/tmp/gc_absdiff_aarch64
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	845
Michalis Spyrou	6e52ba3	2017-10-04 15:40:38 +0100	[diff] [blame]	846	@subsection S3_4_bare_metal Building for bare metal
				847
				848	For bare metal, the library was successfully built using linaros's latest (gcc-linaro-6.3.1-2017.05) bare metal toolchains:
				849	- arm-eabi for armv7a
				850	- aarch64-elf for arm64-v8a
				851
				852	Download linaro for <a href="https://releases.linaro.org/components/toolchain/binaries/6.3-2017.05/arm-eabi/">armv7a</a> and <a href="https://releases.linaro.org/components/toolchain/binaries/6.3-2017.05/aarch64-elf/">arm64-v8a</a>.
				853
				854	@note Make sure to add the toolchains to your PATH: export PATH=$PATH:$MY_TOOLCHAINS/gcc-linaro-6.3.1-2017.05-x86_64_aarch64-elf/bin:$MY_TOOLCHAINS/gcc-linaro-6.3.1-2017.05-x86_64_arm-eabi/bin
				855
				856	@subsubsection S3_4_1_library How to build the library ?
				857
				858	To cross-compile the library with NEON support for baremetal arm64-v8a:
				859
				860	scons Werror=1 -j8 debug=0 neon=1 opencl=0 os=bare_metal arch=arm64-v8a build=cross_compile cppthreads=0 openmp=0 standalone=1
				861
				862	@subsubsection S3_4_2_examples How to manually build the examples ?
				863
				864	Examples are disabled when building for bare metal. If you want to build the examples you need to provide a custom bootcode depending on the target architecture and link against the compute library. More information about bare metal bootcode can be found <a href="http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc.dai0527a/index.html">here</a>.
				865
				866	@subsection S3_5_windows_host Building on a Windows host system
Moritz Pflanzer	07674de	2017-07-21 09:39:36 +0100	[diff] [blame]	867
				868	Using `scons` directly from the Windows command line is known to cause
				869	problems. The reason seems to be that if `scons` is setup for cross-compilation
				870	it gets confused about Windows style paths (using backslashes). Thus it is
				871	recommended to follow one of the options outlined below.
				872
Michalis Spyrou	6e52ba3	2017-10-04 15:40:38 +0100	[diff] [blame]	873	@subsubsection S3_5_1_ubuntu_on_windows Bash on Ubuntu on Windows
Moritz Pflanzer	07674de	2017-07-21 09:39:36 +0100	[diff] [blame]	874
				875	The best and easiest option is to use
				876	<a href="https://msdn.microsoft.com/en-gb/commandline/wsl/about">Ubuntu on Windows</a>.
				877	This feature is still marked as beta and thus might not be available.
				878	However, if it is building the library is as simple as opening a *Bash on
				879	Ubuntu on Windows* shell and following the general guidelines given above.
				880
Michalis Spyrou	6e52ba3	2017-10-04 15:40:38 +0100	[diff] [blame]	881	@subsubsection S3_5_2_cygwin Cygwin
Moritz Pflanzer	07674de	2017-07-21 09:39:36 +0100	[diff] [blame]	882
				883	If the Windows subsystem for Linux is not available <a href="https://www.cygwin.com/">Cygwin</a>
				884	can be used to install and run `scons`. In addition to the default packages
				885	installed by Cygwin `scons` has to be selected in the installer. (`git` might
				886	also be useful but is not strictly required if you already have got the source
				887	code of the library.) Linaro provides pre-built versions of
				888	<a href="http://releases.linaro.org/components/toolchain/binaries/">GCC cross-compilers</a>
				889	that can be used from the Cygwin terminal. When building for Android the
				890	compiler is included in the Android standalone toolchain. After everything has
				891	been set up in the Cygwin terminal the general guide on building the library
				892	can be followed.
				893
Michalis Spyrou	6e52ba3	2017-10-04 15:40:38 +0100	[diff] [blame]	894	@subsection S3_6_cl_stub_library The OpenCL stub library
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	895
				896	In the opencl-1.2-stubs folder you will find the sources to build a stub OpenCL library which then can be used to link your application or arm_compute against.
				897
				898	If you preferred you could retrieve the OpenCL library from your device and link against this one but often this library will have dependencies on a range of system libraries forcing you to link your application against those too even though it is not using them.
				899
				900	@warning This OpenCL library provided is a stub and not a real implementation. You can use it to resolve OpenCL's symbols in arm_compute while building the example but you must make sure the real libOpenCL.so is in your PATH when running the example or it will not work.
				901
				902	To cross-compile the stub OpenCL library simply run:
				903
				904	<target-prefix>-gcc -o libOpenCL.so -Iinclude opencl-1.2-stubs/opencl_stubs.c -fPIC -shared
				905
				906	For example:
				907
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	908	#Linux 32bit
				909	arm-linux-gnueabihf-gcc -o libOpenCL.so -Iinclude opencl-1.2-stubs/opencl_stubs.c -fPIC -shared
				910	#Linux 64bit
				911	aarch64-linux-gnu-gcc -o libOpenCL.so -Iinclude -shared opencl-1.2-stubs/opencl_stubs.c -fPIC
				912	#Android 32bit
				913	arm-linux-androideabi-clang -o libOpenCL.so -Iinclude -shared opencl-1.2-stubs/opencl_stubs.c -fPIC -shared
				914	#Android 64bit
Anthony Barbier	14c86a9	2017-12-14 16:27:41 +0000	[diff] [blame]	915	aarch64-linux-android-clang -o libOpenCL.so -Iinclude -shared opencl-1.2-stubs/opencl_stubs.c -fPIC -shared
				916
				917	@subsection S3_7_gles_stub_library The Linux OpenGLES and EGL stub libraries
				918
				919	In the opengles-3.1-stubs folder you will find the sources to build stub EGL and OpenGLES libraries which then can be used to link your Linux application of arm_compute against.
				920
				921	@note The stub libraries are only needed on Linux. For Android, the NDK toolchains already provide the meta-EGL and meta-GLES libraries.
				922
				923	To cross-compile the stub OpenGLES and EGL libraries simply run:
				924
				925	<target-prefix>-gcc -o libEGL.so -Iinclude/linux opengles-3.1-stubs/EGL.c -fPIC -shared
				926	<target-prefix>-gcc -o libGLESv2.so -Iinclude/linux opengles-3.1-stubs/GLESv2.c -fPIC -shared
				927
				928	#Linux 32bit
				929	arm-linux-gnueabihf-gcc -o libEGL.so -Iinclude/linux opengles-3.1-stubs/EGL.c -fPIC -shared
				930	arm-linux-gnueabihf-gcc -o libGLESv2.so -Iinclude/linux opengles-3.1-stubs/GLESv2.c -fPIC -shared
				931
				932	#Linux 64bit
				933	aarch64-linux-gnu-gcc -o libEGL.so -Iinclude/linux opengles-3.1-stubs/EGL.c -fPIC -shared
				934	aarch64-linux-gnu-gcc -o libGLESv2.so -Iinclude/linux opengles-3.1-stubs/GLESv2.c -fPIC -shared
Anthony Barbier	6ff3b19	2017-09-04 18:44:23 +0100	[diff] [blame]	935	*/