Get started in minutes
Intro to Edge AI
Learn about running AI models directly on embedded devices in real-time.
Learn more →
Quick Start with SL-Series
Get started with Quick Tutorials and embark your Edge AI journey with Machina Dev Kits.
Learn more →
Evaluate Models for SR-Series
Evaluate your models for High-Performance SR-Series AI MCUs.
Learn more →
Models ready to go
Get your project started in minutes with the optimized models preinstalled on Synaptics Astra
Edge AI efficiency
The hardware-aware SyNAP compiler targets the exact NPU or GPU resources available on-chip, which can significantly improve inference speed. There are also advanced optimization options, such as mixed-width and per-channel quantization.
Bring your own model
Have a different model you'd like to bring? Target it to Astra's on-chip NPU or GPU with one command:
- ONNX
- PyTorch
- TensorFlow Lite
$ synap convert --target {$CHIP_MODEL} --model example.onnx
$ synap convert --target {$CHIP_MODEL} --model example.torchscript
$ synap convert --target {$CHIP_MODEL} --model example.tflite
Reference Docs
🤖 SyNAP AI Toolkit
Deep dive into the SyNAP toolkit for building NPU-accelerated apps on SL-Series.
Read more →⚙️ Advanced Optimization
Learn how to convert your existing AI models to run on Synaptics Astra SL-Series.
Read more →💻 Astra SL SDK
Get started with the Synaptics Astra SL-Series SDK documentation.
Read more →