the CMSIS NN software library is a collection of efficient neural
network kernels developed to maximize the performance and minimize
the memory footprint of neural networks on Cortex-M processor cores.
Project https://github.com/ARM-software/CMSIS_5
The library is divided into a number of functions each covering
a specific category:
Convolution Functions
Activation Functions
Fully-connected Layer Functions
SVDF Layer Functions
Pooling Functions
Softmax Functions
Basic math Functions
The library has separate functions for operating on different weight
and activation data types including 8-bit integers (q7_t) and 16-bit
integers (q15_t). The descrition of the kernels are included in the
function description.
More information
https://www.keil.com/pack/doc/CMSIS/NN/html/index.html
Project license : Apache 2.0 License
https://github.com/ARM-software/CMSIS_5/blob/develop/LICENSE.txt
Signed-off-by: Alin Jerpelea <alin.jerpelea@sony.com>
This is a runtime library for inference Neural Network created
by Neural Network Libraries.
Project git: https://github.com/sony/nnabla-c-runtime
It is almost independent from external libraries(depends on C
standard math library) and is written in Pure C (C99).
It has been developed with priority over readability rather than
performance, making it ideal for learning and porting.
It adopts an extensible architecture, and you can use the function
you implemented yourself as necessary for applications that need performance.
Project license : Apache 2.0 License
https://github.com/sony/nnabla-c-runtime/blob/master/LICENSE
Signed-off-by: Alin Jerpelea <alin.jerpelea@sony.com>
