our_knp/claude-memory/knp-wsl-build-state.md

name	description	metadata
knp-wsl-build-state	State of the KNP build in WSL as of 2026-10-07 — CPU works, GPU fails; paths, env, open issues	node_type type originSessionId modified memory project 3960a282-f1ff-5147-91d4-9a2f1014ff08 2026-10-12T11:30:17.531Z

As of 2026-10-07 KNP is built from source in WSL (no sudo). CPU works; GPU backend builds but fails at runtime.

• Build: ~/knp-build (bin/, wheel in knp_python_framework/dist/); OpenCV in ~/deps; CUDA 12.9 in ~/cuda-12.9; GCC 14 via micromamba in ~/mamba; MNIST + logs in ~/run.
• Run env: export LD_LIBRARY_PATH=$HOME/knp-build/bin:$HOME/deps/lib:$HOME/cuda-12.9/lib64:/usr/lib/wsl/lib
• Python 3.14 wheel installed into /mnt/c/KNP/1/.venv; 1/pyproject.toml still points to old 3.11 wheel.
• Build gotchas: -DBoost_PYTHON_VERSION=3.14; disable maybe-uninitialized as error on GCC 15; nvcc 12.9 needs GCC 14.
• MNIST blifat full run on single-threaded CPU: 690 s, 30.9% correct (high precision, low recall); 3000/1000 run gave 47.1%. Multi-threaded backend ~7x slower.
• GPU (RTX 4070 Ti SUPER, sm_89): invalid device function in CUDAMessageBus::unload_messages; GPU backend only supports BLIFATNeuron + DeltaSynapse (no STDP). Changed cuda-backend CMakeLists arch 60 -> "89".
• Open next steps: fix invalid device function; try -m altai; investigate low recall; write Python BLIFAT+Delta net for CPU/GPU.

Why: user ran this work in earlier session(s) and shared the report as context. How to apply: start from this state instead of rebuilding; verify paths still exist before use.

Related: knp-reference-links