📄 This work is described in the scientific paper: https://doi.org/10.1002/cpe.6936
iChess.io v7.27 is a high-performance Convolutional Neural Network (CNN) based Chess & Chess960 engine for play at https://iChess.io, built on top of the Darknet framework. This versatile engine supports multiple AI/ML use cases, such as:
- Chess & Chess960 UCI Engine (AI gameplay)
- Object detection (YOLOv1–v4 on OpenCL)
- Multi-GPU inference and training
- Embedded system deployment (e.g., BeagleBoard AI)
It is fully portable, GPU-accelerated, and compatible with OpenCL, and CPU.
- ✅ Chess AI (UCI) Integration — play chess with AI trained via CNNs
- 🎯 YOLOv2 OpenCL — real-time object detection on multi-GPU setups
- 🔬 Research & Education — train and evaluate CNN models in RAMDisk environments
- 🧠 Computer Vision on Embedded Devices — accelerated inference on edge hardware
# Clone and prepare
mkdir iChess.io.en && cd iChess.io.en
git clone --recursive https://github.com/sowson/darknet
# Build libchess (used in the chess example)
cd darknet/cmake/libchess && mkdir build && cd build
cmake .. && make -j
cp shared/libchess.* ../../../3rdparty/libchess/
# Build engine with chess example enabled
cd ../../../.. && mkdir darknet/build && cd darknet/build
cmake -DDARKNET_ENG_CHESS=1 .. && make -j
# Copy example config and weights
cp ../cfg/chess.cfg ../../ && cp ../weights/chess.weights ../.././iChess.io.en
iChess.io by Piotr Sowa v7.27
position startpos moves e2e4 b8c6 d2d4
go
info depth 1 pv e7e5
bestmove e7e5 ponder e7e5- nlohmann/json
- libchess (used for chess demo)
- ✅ macOS (Intel / Apple Silicon)
- ✅ Ubuntu Linux 20.04+
⚠️ Windows 10/11 (experimental OpenCL build)
https://iblog.isowa.io/2021/11/20/darknet-on-opencl-on-windows-11-x64
-
Run from RAMDisk to reduce disk wear and speed up training/inference:
- Linux:
sudo mount -t tmpfs -o size=4096M tmpfs /your/ramdisk - macOS:
diskutil erasevolume HFS+ "ramdisk" $(hdiutil attach -nomount ram://8388608)
- Linux:
-
Replace clBLAS with CLBlast for improved GEMM performance:
git apply patches/clblast.patch- Darknet-vNext — CUDA-enhanced variant
- YOLO on OpenCL
Created by Piotr Sowa — AI researcher, GPU software engineer, and creator of iChess.io. More information and tutorials at iBlog.isowa.io.
For citations, academic usage, or collaboration inquiries, feel free to reach out via GitHub or LinkedIn.