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