Tengine is a lite, high performance, modular inference engine for embedded device

Efficient Inference of Transformer models

Free TPU for FPGA with compiler supporting Pytorch/Caffe/Darknet/NCNN. An AI processor for using Xilinx FPGA to solve image classification, detection, and segmentation problem.

An open-source project for Windows developers to learn how to add AI with local models and APIs to Windows apps.

Samples code for world class Artificial Intelligence SoCs for computer vision applications.

TinyVision - A Tiny Linux Board / IPC / Server / Router / And so on...

FREE TPU V3plus for FPGA is the free version of a commercial AI processor (EEP-TPU) for Deep Learning EDGE Inference

Easy usage of Rockchip's NPUs found in RK3588 and similar chips

Easier usage of LLMs in Rockchip's NPU on SBCs like Orange Pi 5 and Radxa Rock 5 series

hardware design of universal NPU(CNN accelerator) for various convolution neural network

YoloV5 NPU for the RK3566/68/88

ONNXim is a fast cycle-level simulator that can model multi-core NPUs for DNN inference

Simplified AI runtime integration for mobile app development

C/C++ development kit for Sipeed Maix ecosystem boards

Run your yolov7 object detection with Rockchip NPU platforms (RK3566, RK3568, RK3588, RK3588S, RV1103, RV1106, RK3562).

Advanced driver-assistance system with Google Coral Edge TPU Dev Board / USB Accelerator, Intel Movidius NCS (neural compute stick), Myriad 2/X VPU, Gyrfalcon 2801 Neural Accelerator, NVIDIA Jetson Nano and Khadas VIM3

YoloV8 NPU for the RK3566/68/88

Kotlin bindings for Edgerunner

EmbeddedLLM: API server for Embedded Device Deployment. Currently support CUDA/OpenVINO/IpexLLM/DirectML/CPU

NPUsim: Full-Model, Cycle-Level, and Value-Aware Simulations of NPU Accelerators