Commit Graph

4 Commits

Author SHA1 Message Date
Alin Jerpelea
18609ab1df mlearning: cmsis: enable FPU support
In case of HW with FPU we can benefit from the FPU support.

Signed-off-by: Alin Jerpelea <alin.jerpelea@sony.com>
2022-02-24 11:26:27 -03:00
Alin Jerpelea
0ee15da565 cmsis: build CMSIS support as a module
CMSIS should compile as a module to provide the necessary support
for the dnn test application

Signed-off-by: Alin Jerpelea <alin.jerpelea@sony.com>
2022-02-23 21:57:25 +08:00
Alin Jerpelea
0c69ccea18 libcmsisnn: add the new CHW functionality
The patch for CHW functionality has been added as a result we
can compile the new functions

Signed-off-by: Alin Jerpelea <alin.jerpelea@sony.com>
2022-02-23 21:57:25 +08:00
Alin Jerpelea
5dc7694b17 Add support for CMSIS NN
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>
2022-02-01 19:53:07 +08:00