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Diffstat (limited to 'docs/sections/building.md')
| -rw-r--r-- | docs/sections/building.md | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/docs/sections/building.md b/docs/sections/building.md index 0d6361b..f0c7310 100644 --- a/docs/sections/building.md +++ b/docs/sections/building.md @@ -9,14 +9,14 @@ - [Fetching resource files](#fetching-resource-files) - [Building for default configuration](#building-for-default-configuration) - [Create a build directory](#create-a-build-directory) - - [Configuring the build for MPS3 SSE-300](#configuring-the-build-for-mps3-sse-300) + - [Configuring the build for MPS3 SSE-300](#configuring-the-build-for-mps3-sse_300) - [Using GNU Arm Embedded toolchain](#using-gnu-arm-embedded-toolchain) - [Using Arm Compiler](#using-arm-compiler) - [Generating project for Arm Development Studio](#generating-project-for-arm-development-studio) - [Working with model debugger from Arm Fast Model Tools](#working-with-model-debugger-from-arm-fast-model-tools) - [Configuring with custom TPIP dependencies](#configuring-with-custom-tpip-dependencies) - - [Configuring native unit-test build](#configuring-native-unit-test-build) - - [Configuring the build for simple_platform](#configuring-the-build-for-simple_platform) + - [Configuring native unit-test build](#configuring-native-unit_test-build) + - [Configuring the build for simple-platform](#configuring-the-build-for-simple_platform) - [Building the configured project](#building-the-configured-project) - [Building timing adapter with custom options](#building-timing-adapter-with-custom-options) - [Add custom inputs](#add-custom-inputs) @@ -211,7 +211,7 @@ The build process uses three major steps: 2. Configure the build for the platform chosen. This stage includes: - CMake options configuration - When `<use_case>_MODEL_TFLITE_PATH` build options are not provided, the default neural network models can be - downloaded from [Arm ML-Zoo](https://github.com/ARM-software/ML-zoo/). For native builds, the network input and + downloaded from [Arm ML-Zoo](https://github.com/ARM-software/ML-zoo). For native builds, the network input and output data for tests are downloaded. - Some files such as neural network models, network inputs, and output labels are automatically converted into C/C++ arrays, see: [Automatic file generation](#automatic-file-generation). @@ -412,7 +412,7 @@ bin └── ethos-u-<usecase1> ``` -### Configuring the build for simple_platform +### Configuring the build for simple-platform ```commandline cmake ../ -DTARGET_PLATFORM=simple_platform @@ -549,13 +549,13 @@ For a clock rate of 500MHz, this would translate to: - With a read latency of 64 cycles, and maximum pending reads as 2, each read could be a maximum of 64 or 128 bytes. As defined for the *Ethos-U* NPU AXI bus attribute. - The bandwidth is calculated solely by read parameters: + The bandwidth is calculated solely by read parameters: -  +  - This is higher than the overall bandwidth dictated by the bus parameters of: + This is higher than the overall bandwidth dictated by the bus parameters of: -  +  This suggests that the read operation is only limited by the overall bus bandwidth. @@ -647,8 +647,8 @@ After compiling, your custom model has now replaced the default one in the appli ## Optimize custom model with Vela compiler > **Note:** This tool is not available within this project. It is a Python tool available from -> <https://pypi.org/project/ethos-u-vela/>.\ -The source code is hosted on <https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/>. +> <https://pypi.org/project/ethos-u-vela/>. +> The source code is hosted on <https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/>. The Vela compiler is a tool that can optimize a neural network model into a version that can run on an embedded system containing an *Ethos-U* NPU. |