From 9f95ff5b6ba01db09552b84a0ab79607060a2666 Mon Sep 17 00:00:00 2001 From: Ali Labbene Date: Wed, 11 Dec 2019 08:59:21 +0100 Subject: Official ARM version: v5.4.0 Add CMSIS V5.4.0, please refer to index.html available under \docs folder. Note: content of \CMSIS\Core\Include has been copied under \Include to keep the same structure used in existing projects, and thus avoid projects mass update Note: the following components have been removed from ARM original delivery (as not used in ST packages) - CMSIS_EW2018.pdf - .gitattributes - .gitignore - \Device - \CMSIS - \CoreValidation - \DAP - \Documentation - \DoxyGen - \Driver - \Pack - \RTOS\CMSIS_RTOS_Tutorial.pdf - \RTOS\RTX - \RTOS\Template - \RTOS2\RTX - \Utilities - All ARM/GCC projects files are deleted from \DSP, \RTOS and \RTOS2 Change-Id: Ia026c3f0f0d016627a4fb5a9032852c33d24b4d3 --- docs/NN/html/index.html | 163 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 163 insertions(+) create mode 100644 docs/NN/html/index.html (limited to 'docs/NN/html/index.html') diff --git a/docs/NN/html/index.html b/docs/NN/html/index.html new file mode 100644 index 0000000..965e6d3 --- /dev/null +++ b/docs/NN/html/index.html @@ -0,0 +1,163 @@ + + + + + +CMSIS NN Software Library +CMSIS-NN: CMSIS NN Software Library + + + + + + + + + + + + + + +
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CMSIS-NN +  Version 1.1.0 +
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CMSIS NN Software Library
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CMSIS NN Software Library
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Introduction

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This user manual describes the CMSIS NN software library, 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.

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The library is divided into a number of functions each covering a specific category:

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  • Neural Network Convolution Functions
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  • Neural Network Activation Functions
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  • Fully-connected Layer Functions
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  • Neural Network Pooling Functions
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  • Softmax Functions
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  • Neural Network Support Functions
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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. The implementation details are also described in this paper [1].

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Block Diagram

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+CMSIS-NN-OVERVIEW.PNG +
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Examples

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The library ships with a number of examples which demonstrate how to use the library functions.

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Pre-processor Macros

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Each library project have differant pre-processor macros.

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  • ARM_MATH_DSP:
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Define macro ARM_MATH_DSP, If the silicon supports DSP instructions.

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  • ARM_MATH_BIG_ENDIAN:
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Define macro ARM_MATH_BIG_ENDIAN to build the library for big endian targets. By default library builds for little endian targets.

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  • ARM_NN_TRUNCATE:
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Define macro ARM_NN_TRUNCATE to use floor instead of round-to-the-nearest-int for the computation.

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Copyright Notice

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Copyright (C) 2010-2018 Arm Limited. All rights reserved.

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[1] CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs https://arxiv.org/abs/1801.06601

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