- Docker: Delete 23 deprecated Dockerfiles, fix CI/CD to use Dockerfile.foxhunt-build - Config: Remove 36 .env files, keep 4 essential, delete config/environments/ - Docs: Archive 614 Wave D files to docs/archive/wave_d/, 95% reduction in root - Scripts: Delete 56 deprecated scripts, keep 58 production-critical (49% reduction) - Python: Organize 37 scripts into scripts/python/ subdirectories, delete ml/python/ - Build: Remove 1GB artifacts, delete old venvs, clean Python cache from git - Migrations: Delete deprecated directory (4,432 lines), remove duplicate database/migrations/ - Infrastructure: Delete deployment/ (61 files), docs/scripts/ (8 files) Total impact: ~2,500 files cleaned, 750MB+ space freed, zero production impact All deleted scripts backed up to archives. runpod/ and tests/runpod/ preserved. data_acquisition_service retained per user request.
3.0 KiB
==================================================================== DETAILED CUDA 12.9 VERIFICATION REPORT
BINARY LOCATIONS (Absolute Paths)
/home/jgrusewski/Work/foxhunt/target/release/examples/train_mamba2_parquet /home/jgrusewski/Work/foxhunt/target/release/examples/train_tft_parquet /home/jgrusewski/Work/foxhunt/target/release/examples/train_dqn /home/jgrusewski/Work/foxhunt/target/release/examples/train_ppo
LIBRARY DEPENDENCY ANALYSIS (ldd output)
train_mamba2_parquet CUDA libraries: libcuda.so.1 => /lib/x86_64-linux-gnu/libcuda.so.1 (0x00007a6b418fd000) libcurand.so.10 => /usr/local/cuda-12.9/lib64/libcurand.so.10 (0x00007a6b37000000) libcublas.so.12 => /usr/local/cuda-12.9/lib64/libcublas.so.12 (0x00007a6b30800000) libcublasLt.so.12 => /usr/local/cuda-12.9/lib64/libcublasLt.so.12 (0x00007a6afde00000)
train_tft_parquet CUDA libraries: libcuda.so.1 => /lib/x86_64-linux-gnu/libcuda.so.1 (0x0000725c8f530000) libcurand.so.10 => /usr/local/cuda-12.9/lib64/libcurand.so.10 (0x0000725c84c00000) libcublas.so.12 => /usr/local/cuda-12.9/lib64/libcublas.so.12 (0x0000725c7e400000) libcublasLt.so.12 => /usr/local/cuda-12.9/lib64/libcublasLt.so.12 (0x0000725c4ba00000)
train_dqn CUDA libraries: libcuda.so.1 => /lib/x86_64-linux-gnu/libcuda.so.1 (0x00007b013af68000) libcurand.so.10 => /usr/local/cuda-12.9/lib64/libcurand.so.10 (0x00007b0130600000) libcublas.so.12 => /usr/local/cuda-12.9/lib64/libcublas.so.12 (0x00007b0129e00000) libcublasLt.so.12 => /usr/local/cuda-12.9/lib64/libcublasLt.so.12 (0x00007b00f7400000)
train_ppo CUDA libraries: libcuda.so.1 => /lib/x86_64-linux-gnu/libcuda.so.1 (0x00007f1ffbceb000) libcurand.so.10 => /usr/local/cuda-12.9/lib64/libcurand.so.10 (0x00007f1ff1400000) libcublas.so.12 => /usr/local/cuda-12.9/lib64/libcublas.so.12 (0x00007f1feac00000) libcublasLt.so.12 => /usr/local/cuda-12.9/lib64/libcublasLt.so.12 (0x00007f1fb8200000)
VERIFICATION SUMMARY
✅ All binaries link to /usr/local/cuda-12.9/lib64/ libraries ✅ No references to cuda-13.0 libraries found ✅ Critical libraries verified:
- libcublas.so.12 (NOT libcublas.so.13)
- libcublasLt.so.12
- libcurand.so.10
RUNPOD COMPATIBILITY
Runpod Docker Container CUDA Version: 12.9.1 Local Compilation CUDA Version: 12.9 Binary CUDA Linkage: 12.9 (libcublas.so.12)
Expected Runtime Behavior: ✅ Binaries will find libcublas.so.12 in Runpod container ✅ No "cannot open shared object file" errors ✅ Full CUDA GPU acceleration enabled
Previous Issue (FIXED): ❌ Binaries linked to libcublas.so.13 (not available in Runpod) ✅ Now linked to libcublas.so.12 (available in Runpod CUDA 12.9.1)
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