Minimal

After installation, start here to confirm your Neat setup is wired correctly.

This page keeps the first run intentionally small: create a tiny app, confirm the headers/imports resolve and it builds, and run it on the DevKit to confirm the runtime responds. Once this works, continue to Run an App to run a real model inside a small Graph application.

Neat SDK Prerequisite

To run commands on the DevKit directly from inside the SDK (for example, dk build/sima_neat_hello or dk hello_neat.py), set up DevKit pairing first.

Required setup: Pair the Neat SDK with a DevKit

Minimal application

Create a working directory for the example, then use the Python / C++ tabs to follow your language. Your choice follows the site-wide language selector, so it stays consistent across the docs.

Create two files:

CMakeLists.txt tells CMake how to build and link the app.

CMakeLists.txt
cmake_minimum_required(VERSION 3.16)
project(sima_neat_hello LANGUAGES CXX)

set(CMAKE_CXX_STANDARD 20)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS OFF)

# Supports both:
# - DevKit/native installs (system paths)
# - Cross builds with SYSROOT exported (SDK sysroot paths)
if(DEFINED ENV{SYSROOT} AND NOT "$ENV{SYSROOT}" STREQUAL "")
  list(APPEND CMAKE_PREFIX_PATH
    "$ENV{SYSROOT}/usr"
    "$ENV{SYSROOT}/usr/lib"
    "$ENV{SYSROOT}/usr/lib/aarch64-linux-gnu"
  )
endif()

find_package(SimaNeat REQUIRED CONFIG)
find_package(PkgConfig REQUIRED)
pkg_check_modules(OPENCV REQUIRED IMPORTED_TARGET opencv4)

add_executable(sima_neat_hello main.cpp)
target_link_libraries(sima_neat_hello
  PRIVATE
    SimaNeat::sima_neat
    PkgConfig::OPENCV
)

main.cpp contains the tiny Neat program.

main.cpp
#include <iostream>
#include <pipeline/TensorCore.h>

int main() {
  auto storage = simaai::neat::make_cpu_owned_storage(64);
  if (!storage) {
    std::cerr << "Failed to allocate CPU tensor storage\n";
    return 1;
  }
  std::cout << "Hello from sima-neat\n";
  return 0;
}

Your working directory should look like this:

sima-neat-hello/
├── CMakeLists.txt
└── main.cpp

Build the example:

cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -j

Run:

On the DevKit
```
./build/sima_neat_hello
```
On the Neat SDK from host
```
dk build/sima_neat_hello
```

You should see:

Hello from sima-neat

If the program builds, the imports resolve, and it prints the greeting, your Neat installation is ready.

About dk / devkit-run

dk (alias for devkit-run) is a shell function in the SDK container, defined in ~/devkit-sync.rc and loaded by ~/.bashrc.

Because it is a shell function, commands such as which devkit-run may return nothing in the SDK shell. Use dk <file> to execute a built binary or Python entry-point file on the paired DevKit.

Once the minimal app works, continue with Run an App to run a real object-detection model inside a small Graph application.

Minimal application​

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Minimal application

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