CMSIS-NN
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The document provides an overview of cmsis-nn, a software library designed for running neural networks on ARM Cortex-M microcontrollers. It includes information on supported functions like convolution, activation, pooling, and softmax, as well as data types and CPU requirements. Additionally, examples and performance details for applications like CIFAR-10 are presented.
CMSIS-NN
- 1. CMSIS-NN, INTRO ÐÂ?Öñ´aÞr Anthony Liu, 2018/03/08 1
- 2. RESOURCES ? Source: https://github.com/ARM-software/CMSIS_5 ? Web 1: https://developer.arm.com/embedded/cmsis ? Web 2: http://www2.keil.com/mdk5/cmsis/ ? Paper: https://arxiv.org/abs/1801.06601 ? Manual: http://arm-software.github.io/CMSIS_5/NN/html/ index.html 2
- 3. CMSIS 5.3.0 ? http://www2.keil.com/mdk5/cmsis/ ? https://developer.arm.com/embedded/cmsis ? Cortex Microcontroller Software Interface Standard ? CMSIS-NN ?rst appeared in 5.2.1 dev 3 CMSIS-CORE CMSIS-RTOS CMSIS-DSP CMSIS-Driver CMSIS-SVD CMSIS-DAP CMSIS-Pack CMSIS-NNCMSIS-Zone (planned) 3
- 5. CMSIS-NN ? DSP: Cortex-M0 (N) / Cortex-M3 (N) Cortex-M4 (Y) / Cortex-M7 (Y) / Cortex-M33 (Optional) ? For inference only with limited computation power ? CPU: Dozens MHz to 192MHz Cortex-M4, 400 MHz Cortex-M7 ? MEMORY: Dozens KB to a few MB ? Kernels Support: q7t and q15_t fractional data type: [ -1.0, 1.0 ) ? Functions ? Neural Network Convolution Functions ? Neural Network Activation Functions ? Fully-connected Layer Functions ? Neural Network Pooling Functions ? Softmax Functions 5
- 6. SUPPORT ? Data conversion ? arm_q7_to_q15_no_shift ? arm_q7_to_q15_reordered_no_shift 6
- 7. CONVOLUTION ? arm_convolve_HWC_q7_basic ? arm_convolve_HWC_q15_basic ? arm_convolve_HWC_q7_fast ? arm_convolve_HWC_q7_fast_nonsquare ? arm_convolve_HWC_q7_RGB ? arm_convolve_HWC_q15_fast ? arm_convolve_1x1_HWC_q7_fast_nonsquare ? arm_depthwise_separable_conv_HWC_q7 ? arm_depthwise_separable_conv_HWC_q7_nonsquare 7
- 8. ACTIVATION ? ReLU ? arm_relu_q7 ? arm_relu_q15 ? Sigmoid / Tanh ? arm_nn_activations_direct_q7 ? arm_nn_activations_direct_q15 8
- 9. POOLING ? Supports 1.7 format max-pooling and average-pooling ? arm_maxpool_q7_HWC ? arm_avepool_q7_HWC 9
- 10. SOFTMAX ? EXP(2) based softmax function ? arm_softmax_q7 ? arm_softmax_q15 10
- 11. FULLY-CONNECTED LAYER ? arm_fully_connected_q7 ? arm_fully_connected_q7_opt ? arm_fully_connected_q15 ? arm_fully_connected_q15_opt ? arm_fully_connected_mat_q7_vec_q15 ? arm_fully_connected_mat_q7_vec_q15_opt 11
- 12. FOOTPRINT - 9,306 text data bss dec hex filename 132 0 0 132 84 ./SoftmaxFunctions/arm_softmax_q15.o 154 0 0 154 9a ./SoftmaxFunctions/arm_softmax_q7.o 544 0 0 544 220 ./PoolingFunctions/arm_pool_q7_HWC.o 2816 0 0 2816 b00 ./NNSupportFunctions/arm_nntables.o 84 0 0 84 54 ./NNSupportFunctions/arm_q7_to_q15_no_shift.o 72 0 0 72 48 ./NNSupportFunctions/arm_q7_to_q15_reordered_no_shift.o 102 0 0 102 66 ./FullyConnectedFunctions/arm_fully_connected_q15.o 88 0 0 88 58 ./FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15.o 476 0 0 476 1dc ./FullyConnectedFunctions/arm_fully_connected_mat_q7_vec_q15_opt.o 486 0 0 486 1e6 ./FullyConnectedFunctions/arm_fully_connected_q15_opt.o 86 0 0 86 56 ./FullyConnectedFunctions/arm_fully_connected_q7.o 532 0 0 532 214 ./FullyConnectedFunctions/arm_fully_connected_q7_opt.o 266 0 0 266 10a ./ConvolutionFunctions/arm_convolve_1x1_HWC_q7_fast_nonsquare.o 404 0 0 404 194 ./ConvolutionFunctions/arm_convolve_HWC_q15_basic.o 450 0 0 450 1c2 ./ConvolutionFunctions/arm_convolve_HWC_q15_fast.o 426 0 0 426 1aa ./ConvolutionFunctions/arm_convolve_HWC_q7_basic.o 434 0 0 434 1b2 ./ConvolutionFunctions/arm_convolve_HWC_q7_fast.o 434 0 0 434 1b2 ./ConvolutionFunctions/arm_convolve_HWC_q7_fast_nonsquare.o 428 0 0 428 1ac ./ConvolutionFunctions/arm_convolve_HWC_q7_RGB.o 298 0 0 298 12a ./ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7.o 378 0 0 378 17a ./ConvolutionFunctions/arm_depthwise_separable_conv_HWC_q7_nonsquare.o 4 0 0 4 4 ./ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15.o 4 0 0 4 4 ./ConvolutionFunctions/arm_nn_mat_mult_kernel_q7_q15_reordered.o 104 0 0 104 68 ./ActivationFunctions/arm_nn_activations_q15.o 48 0 0 48 30 ./ActivationFunctions/arm_nn_activations_q7.o 28 0 0 28 1c ./ActivationFunctions/arm_relu_q15.o 28 0 0 28 1c ./ActivationFunctions/arm_relu_q7.o
- 13. EXAMPLE - CIFAR-10 ? arm_convolve_HWC_q7_RGB() ? arm_relu_q7() ? arm_maxpool_q7_HWC() ? arm_convolve_HWC_q7_fast() ? arm_relu_q7() ? arm_avepool_q7_HWC() 13 ? arm_convolve_HWC_q7_fast() ? arm_relu_q7() ? arm_avepool_q7_HWC() ? arm_fully_connected_q7() ? arm_softmax_q7() ? conv1_wt: 2,400 ? conv1_bias: 32 ? conv2_wt: 12,800 ? conv2_bias: 16 ? conv3_wt: 12,800 ? conv3_bias: 32 ? ip1_wt: 10 ? ip1_bias: 10 ? input_data: 3K ? output_data: 10 ? col_buffer: 3,200 ? scratch_buffer: 40K
- 14. PERFORMANCE CIFAR-10 speed show case GRU power-save show case