AI Developer
Synaptics Astra™ equips developers with best-in-class edge AI hardware and open-source tools - for product innovation with a proven path to scale.
Tutorials
Get started
Get started today with embedded AI models optimized for Synaptics Astra GPU and NPU.
Learn more →
Build apps with Ultralytics YOLO
Compile YOLO11, YOLOv8 for edge computer vision applications.
Learn more →
Optimize models for NPU
Optimize models for NPU-accelerated MPUs and MCUs that are cost and power efficient.
Learn more →
Technical Blogs
LLMs and SLMs on Astra
LLMs, SLMs, and embedded AI are the future of AI development. Learn how to get started with Synaptics Astra AI Developer.
Learn more →
Whisper on Astra
In the realm of real-time speech recognition, OpenAI's Whisper models have been state-of-the-art, offering developers the ability to transcribe audio efficiently.
Learn more →
YOLOv8 Instance Segmentation
Learn how real-time instance segmentation works using YOLOv8 model on Astra Machina SL1680 board.
Learn more →
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
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.
Reference Docs
🤖 SyNAP AI Toolkit
Deep dive into the SyNAP toolkit for building NPU-accelerated apps.
Read more →⚙️ Advanced Optimization
Learn how to convert your existing AI models to run on Synaptics Astra.
Read more →💻 Astra SDK
Build C++ applications with accelerated AI inference using on-device NPU
Read more →