*Compute Library for Deep Neural Networks* (*clDNN*) is an open source performance
library for Deep Learning (DL) applications intended for acceleration of
DL Inference on Intel® Processor Graphics – including HD Graphics and
-Iris® Graphics.
+Iris® Graphics.
*clDNN* includes highly optimized building blocks for implementation of
convolutional neural networks (CNN) with C and C++ interfaces. We created
this project to enable the DL community to innovate on Intel® processors.
clDNN uses 3<sup>rd</sup>-party components licensed under following licenses:
- *googletest* under [Google\* License](https://github.com/google/googletest/blob/master/googletest/LICENSE)
- *OpenCL™ ICD and C++ Wrapper* under [Khronos™ License](https://github.com/KhronosGroup/OpenCL-CLHPP/blob/master/LICENSE.txt)
+- *RapidJSON* under [Tencent\* License](https://github.com/Tencent/rapidjson/blob/master/license.txt)
## Documentation
The latest clDNN documentation is at [GitHub pages](https://intel.github.io/clDNN/index.html).
You can find more information [here](https://software.intel.com/en-us/openvino-toolkit/deep-learning-cv).
+## OpenVINO specific changes
+ New features:
+ - added `not` activation type
+ - added `depth_to_space` layer
+ - new clip options in `detection_output` (cpu impl) and `proposal` layers
+ - added eltwise `xor` and `squared_diff` operations
+ - added `gather` layer
+ - added `bilinear` mode for position sensitive `roi_pooling` layer
+ - added `shuffle_channels` layer
+ - added `strided_slice` layer
+ - added IE gates ordering for lstm layer
+ - added `reverse_sequence` layer
+ Bug fixes:
+ - fixed unknown bool type error in C API
+ - fixed non-relu activation fusing with conv_eltwise node
+ - fixed infinite performance regression on several topologies
+ - minor internal fixes
+ - unified the permute order with cldnn's tensor order
+ Other:
+ - removed boost
+ - supported compilation with c++11 only
+
+
## Changelog
+### Drop 13.1
+ New features:
+ - added max mode for contract primitive
+ - added one_hot primitive
+ - optional explicit output data type support for all primitives
+ Bug fixes:
+ - fix for graph optimizer (crop primitive)
+ - fix for processing order (deconvolution primitive)
+ - fix for convolution-eltwise primitive
+ UX:
+ - cache.json is searched in to library directory
+ Performance:
+ - optimizations for lstm_gemm primitive
+
+### Drop 13.0
+ New features:
+ - events pool
+ - group support in convolution and deconvolution primitives
+ - broadcastable inputs support for eltwise primitive
+ - asymmetric padding for convolution primitive
+ - fused convolution-eltwise primitive (API extension)
+ - auto-calculated output shape support for reshape primitive
+ - crop support for i8/s8/i32/i64 types
+ - broadcast axis support for broadcast primitive
+ - logic and comparison operations support for eltwise primitive
+ Bug fixes:
+ - added required alignment checks for some fc implementations
+ - added lstm support for f16 (half) type
+ - reorders for fc moved to graph compiler
+ - primitive fusing and reorder fixes
+ UX:
+ - added internal core tests project
+ - refactored optimizations pass manager and passes
+ Performance:
+ - optimized concatenation during upsampling (unpool)
+ - IMAD-based optimizations for convolution, fc, eltwise and pooling primitives (i8/s8)
+ - convolution-eltwise fusing optimizations
+ - partial writes optimizations for block-based kernels
+
+### Drop 12.1
+ - gtests code refactor
+ - buildbreak fix
+
+### Drop 12.0
+ New features:
+ - pyramidRoiAlign primitive
+ - multiple axes support for reverse mode in index_select
+ - eltwise min/max/mod support for i8/i32/i64
+ - broadcast support for i32/i64
+ Bug fixes:
+ - memory leak fixes
+ - in-place reshape
+ - no padding for output primitives
+ UX:
+ - RapidJSON library for auto-tune cache
+ - less dependencies in program.cpp
+ - do not throw error, when device not validated
+ - global pooling in c API
+ - optimized padding for convolution
+
+### Drop 11.0
+ New features:
+ - throttle hints
+ - extended border and tile
+ - GPU implementation of Detection Output
+ - More cases for BatchNorm primitive
+ Bug fixes:
+ - GEMM fix (align with ONNX)
+ - memory leak fix in memory pool
+ - increase FC precision for fp16 (fp32 accu)
+ Performance:
+ - cache for new topologies and devices
+ - conv1x1 with stride >1 into eltwise optimization
+
+### Drop 10.0
+ New features:
+ - condition primitive
+ - fused convolution with bn and scale (backprop)
+ - scale/shit and mean/var as an output in batch norm
+ - add LSTM output selection
+ Bug fixes:
+ - memory pool fixes
+ UX:
+ - downgrade to cxx11
+ - add support for u8 data type in custom primitive
+ - library size optimizations
+ Performance:
+ - in place concatenation optimization
+ - conv1x1 with stride >1 into eltwise optimization
+
+### Drop 9.2
+ New features
+ - local convolution
+ - eltwise with strie
+
### Drop 9.1
New features:
- select index primitive
- reorder optimization
- concatenation optimization
- eltwise optimization
- - activation fusing
+ - activation fusing
### Drop 3.0
Added:
- initial drop of clDNN
## Support
-Please report issues and suggestions
+Please report issues and suggestions
[GitHub issues](https://github.com/01org/cldnn/issues).
## How to Contribute
* Intel® Iris® Graphics 650 (GT3e, *client* market)
* Intel® HD Graphics P630 (GT2, *server* market)
* Intel® Iris® Pro Graphics 630 (GT2, *server* market)
-
+
clDNN currently uses OpenCL™ with multiple Intel® OpenCL™ extensions and requires Intel® Graphics Driver to run.
clDNN requires CPU with Intel® SSE/Intel® AVX support.
---
The software dependencies are:
-- [CMake\*](https://cmake.org/download/) 3.5 or later
+- [CMake\*](https://cmake.org/download/) 3.5 or later
- C++ compiler with C++11 standard support compatible with:
- * GNU\* Compiler Collection 4.8 or later
+ * GNU\* Compiler Collection 4.8 or later
* clang 3.5 or later
* [Intel® C++ Compiler](https://software.intel.com/en-us/intel-parallel-studio-xe) 17.0 or later
* Visual C++ 2015 (MSVC++ 19.0) or later
> Intel® CPU intrinsics header (`<immintrin.h>`) must be available during compilation.
- [python™](https://www.python.org/downloads/) 2.7 or later (scripts are both compatible with python™ 2.7.x and python™ 3.x)
-- *(optional)* [Doxygen\*](http://www.stack.nl/~dimitri/doxygen/download.html) 1.8.13 or later
+- *(optional)* [Doxygen\*](http://www.stack.nl/~dimitri/doxygen/download.html) 1.8.13 or later
Needed for manual generation of documentation from inline comments or running `docs` custom target which will generate it automatically.
-> [GraphViz\*](http://www.graphviz.org/Download..php) (2.38 or later) is also recommended to generate documentation with all embedded diagrams.
+> [GraphViz\*](http://www.graphviz.org/Download..php) (2.38 or later) is also recommended to generate documentation with all embedded diagrams.
(Make sure that `dot` application is visible in the `PATH` environment variable.)
---
---
-clDNN uses a CMake-based build system. You can use CMake command-line tool or CMake GUI (`cmake-gui`) to generate required solution.
+clDNN uses a CMake-based build system. You can use CMake command-line tool or CMake GUI (`cmake-gui`) to generate required solution.
For Windows system, you can call in `cmd` (or `powershell`):
```shellscript
@REM Generate 32-bit solution (solution contains multiple build configurations)...
cmake -E make_directory build && cd build && cmake -G "Visual Studio 14 2015" ..
@REM Generate 64-bit solution (solution contains multiple build configurations)...
cmake -E make_directory build && cd build && cmake -G "Visual Studio 14 2015 Win64" ..
-```
+```
Created solution can be opened in Visual Studio 2015 or built using appropriate `msbuild` tool
(you can also use `cmake --build .` to select build tool automatically).
| CLDNN__RUN_TESTS | BOOL | Run tests after building `tests` project. This option requires `CLDNN__INCLUDE_TESTS` option to be `ON`. Default: `OFF` |
| | | |
| CLDNN__CMAKE_DEBUG | BOOL | Enable extended debug messages in CMake. Default: `OFF` |
-
+
---
clDNN includes unit tests implemented using the googletest framework. To validate your build, run `tests` target, e.g.:
projects / platform / upstream / dldt.git / blobdiff