# 概述

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i2oJ/j3FbkpV+IuDxkvJBJKIgQ4B/tRtAtPXCPVIL4qb50x4Q9Z9g4fKk2YoVPheIrT0IvgnItkIYJnbIfqYwL0MVD2CDfLvJUYFXG5SHjhUxCIa2QR1g6k6CbqYsWKUlRmOpLcVQb6NL8huxmLKIJlGYcOO0tT1MdpGFCJw1AHIW9R2Cu9FGsJiLBAfkh48VMQkGEAPE53mNet4BUgtowf56W7nijAhttMFHb9egUB55LuPSC31v5x9gxQ/RAKiZ0yn4Yb6D4TGCu9FGsGOJgBp92gdTyFUSwSI92w+sWcG/eljocHdE24hDuzpYX24ligx++S7j0QbonXBrkg1euBlIxoZMOKNEy3uTALR7aqrQuJZJqRsb1IeMZzYIIFhSOnXSLSCWox4t4dzZ/+zazlEsffJdw6YN0T7g0yAevXA2kYUInFYACMz1/ZUDLG2WgQ6NOjjshPmR8zDjpFhFLUG8X/tYBabGdzGAf8UCsPsqP+OGDcE+4OMgHr1x3L1IYUAE1w1iLAS1vlAnBtOe+BY4Is3JRsHiWasMFJ9290Zc0pRt0HlMNTEGhUagp0NQEbHdBo+0/hpIpc6Br3q+2BbjBuDe5zXD2DNbthlSCNsOSggmdMo2YR2HlFCDIWAQsVs6Wtns9wdo5UKtJEsGCfU4HJON0i0glaDMsaZjQSQWMIK9Rh1FqpgUcSJ5pC3LC5SHjuUxCQYTffbGCbvLHwEglaDMsaZjQKevh0weAxGkEegAbFuy5yXEOJr2s7PKQ8XwmoZRWyIO0knG0JN3CA/cISYqbYknDhE6ZD4nNBHTai0APYMNCgycLtbLLQ8azmYRSWqEA+2g3om6afIgQkhR7zQBANtBF+3weEjTy7cRbvkE0g3NXAEDhPwVEdBYr/Kfwn8J/Cv8p/Kfwn8J/Cv8p/Kfwn8J/vmyYJYDXQA12vD8vQv9xTcST4SgvQjQMirB9+RG2gR42nZjLjxAdBDV4fke0iYxTeuA1gO1B0n9QCz+zOwqPFdszoQebDYxZgKOKONoth5ePqQvm0sl9AIpgKQrTtg4eV8DX7sMuV3tAOQangvP5KVV0TcwqPh8T4ESUTvZqolYd74+CtfMrGW/odyo/L+2+4LgX4HXQgg1H4dmQJhhMKUvHFVGt7o26bdsNcEwN52jblH4tEZX7nWEOcHNMDexMKdEe1OGqAk7Odt1EQxqoca+jfveDAbr8gBouc8FgFKINgBpsIEoGPVUrgJNLUffN/Gk1HNJCbMX2qyGenJ4PkrkhLTA0m16iradUwIHZqBu3/n3HVZAfsiNQn+84oQGO7ws2dWSPDurbnihKMVF0fsferLeV/qhrt5U9ezPedi8H7PLl3Vnv8j0r6q9vyZFntMJ/Cv8p/Kfwn8J/Cv8p/Kfwn8J/Cv8p/Kfwn8J/ig249Rt5VK79fr6Tb9zqxg+vynfyo6vduOiWXOfHr916iRvmq7f+9Fu5zX/9wa3fNK528ZW33JHTtFuvucTkXc0AAA==)

一起来观看本次培训课程，该培训重点介绍 Qualcomm Linux AI 开发者工作流。

这是专为物联网领域的开发者和专业人士量身定制的，满足您对基于Qualcomm 平台上提高部署设备上 AI 解决方案的理解和技能。

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    <div class='topic-detail'><div class='topic-updated-date'><span> Last Published: </span>Oct 12, 2025</div><div class='prev-and-next-links'><span class='previous-topic-link'><span aria-hidden='true' class='disabled' data-tip='' data-effect='solid'></span></span></div></div></body>
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Qualcomm Linux 中的 AI/ML 开发者工作流主要分为两个步骤：

| 第 1 步<br><br><br>编译并优化模型 | <ul class="simple"><br><li><p>编译并优化来自第三方 AI 框架的模型，以便在 Qualcomm 硬件上高效运行。例如，可以将 Tensorflow 模型导出到 LiteRT 模型。</p></li><br><li><p>或者，使用硬件特定的定制对性能和精确度进行量化和微调。</p></li><br></ul> |
| --- | --- |
| 第 2 步<br><br><br>编译应用程序，使用优化后的模型运行设备推理 | <ul class="simple"><br><li><p>将 AI 模型集成到用例 pipeline 中。</p></li><br><li><p>交叉编译应用程序，用以生成使用依赖库的可执行二进制文件。</p></li><br></ul> |

Important

- 确保主机使用 Ubuntu 22.04。
- 本文档中的命令与 Qualcomm Linux 1.5 兼容。

    通过运行[开发套件用户指南](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-251/set_up_the_device.html#verify-the-qualcomm-linux-version)中的命令来验证您的 Qualcomm Linux 发布版本

    如果您的发布版本不是 1.5，请[更新软件](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-251/upgrade-rb3gen2-software.html#upgrade-rb3gen2-software)。
- 本文档中的示例应用程序和 AI 程序与[支持的版本兼容](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-51/introduction.html#supported-component-versions)。

    在开始 AI/ML 开发之前，请确保将匹配的 SDK 下载到主机。

## AI 架构

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)

开发者可以从 ONNX、PyTorch、TensorFlow 或 TFLite 引入模型，并使用 Qualcomm AI SDK 在 Qualcomm AI 硬件 - HTP (NPU)、GPU、CPU 上高效运行这些模型。

## AI 硬件

- **Qualcomm Kryo™ CPU**：业界领先的 CPU，具有高性能和卓越能效。
- **Qualcomm Adreno GPU**：适合以平衡的功耗和性能运行 AI 工作负载。AI 工作负载可以通过 OpenCL 内核进行加速。GPU 还可用于加速模型预处理/后处理。
- **Qualcomm Hexagon 张量处理器 (HTP)**：又称 NPU/DSP/HMX，适合以低功耗、高性能执行 AI 工作负载。为优化性能，需要对预训练模型进行量化，使其达到支持的任一种精度。

## AI 软件

AI 堆栈包含各种 SDK，以便利用 AI 硬件加速器的强大功能。开发者可以使用自己选择的一种 SDK 来部署 AI 工作负载。预训练模型（TFLite 模型除外）在运行之前需要使用所选 SDK 将其转换为可执行格式。LiteRT 模型可以使用 TFLite Delegate 直接运行。

TFLite

LiteRT 模型可以使用以下 Delegate 在具有加速的 Qualcomm 硬件上本地运行。

| Delegate | 加速 |
| --- | --- |
| AI Engine Direct Delegate (QNN Delegate) | CPU、GPU 和 HTP |
| XNNPACK Delegate | CPU |
| GPU Delegate | GPU |

Qualcomm Neural Processing Engine SDK (SNPE)

Qualcomm Neural Processing Engine (SNPE) 是一种用于执行深度神经网络的软件加速 runtime。SNPE 提供相关工具来对神经网络进行转换、量化，并在 CPU、GPU 和 HTP 等硬件加速器上对其进行加速。

Qualcomm AI Engine Direct (QNN)

Qualcomm AI Engine Direct 是 Qualcomm 芯片组和 AI 加速核心中适用于 AI/ML 用例场景的一种软件架构。该架构旨在提供统一的 API，模块化和可扩展的预加速库，从而基于这种可重用的结构打造全栈 AI 解决方案。它为 Qualcomm Neural Processing SDK、LiteRT AI Engine Direct Delegate 等 runtime 提供支持。

AI Model Efficiency Toolkit (AIMET)

用于优化（压缩和量化）训练后的神经网络模型的开源库。这是一个复杂的 SDK，旨在生成优化的量化模型，仅供高级开发者使用。

Last Published: Oct 12, 2025

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