environment.yml

# HPC-Performance-AI project-local Conda environment.
#
# Every package is pinned to the exact version the benchmark suite was
# validated with, so `./setup_env.sh` reproduces the same user-space
# toolchain on any Linux x86_64 machine. Create/update via ./setup_env.sh
# (installs into <repo>/.conda_env; never touches conda base or $HOME).
#
# Deliberately NOT managed by Conda (system GPU toolchain, see README):
#   NVIDIA driver / CUDA Toolkit / NVCC / Nsight Compute / ROCm / hipcc
name: hpcperf
channels:
  - conda-forge
dependencies:
  - python=3.12.3
  - cmake=3.28.4
  - ninja=1.13.2
  - pip=26.2.1
  - gcc_linux-64=13.3.0        # NVCC host compiler (validated with CUDA 13.2)
  - gxx_linux-64=13.3.0
  - numpy=2.5.2                # used by the verify.py correctness checks
  - scipy=1.18.0
  - perl=5.32.1                # runs .tools/bin/cloc (cloc is not on conda-forge)
  - pyyaml=6.0.3               # Level 3 harness tools (source locks, benchmark.yaml, freeze specs, workspace checks)
  # ---- Level 2 mini-app dependencies (added 2026-09-01) ----------------------
  # CUDA-aware Open MPI (conda-forge "cuda" build variant, pinned by build
  # string so the solver picks the same variant on every machine).
  - openmpi=5.0.10=hee33aa4_2
  - metis=5.1.0                # MFEM / Branson mesh partitioning
  - yaml-cpp=0.8.0             # Kripke / SHAW input parsing
  - openblas=0.3.34            # hipBone
  - fftw=3.3.11=mpi_openmpi_*  # heFFTe (Cabana) CPU backend
  - hdf5=2.2.0=mpi_openmpi_*   # parallel HDF5 (Cabana / ExaMPM / branson optional)
  - libpnetcdf=1.15.0=mpi_openmpi_*  # miniWeather output
  - libnetcdf=4.10.1=mpi_openmpi_*   # Exodus/Ioss inside the Trilinos build for MiniEM (level2/miniem)
  - gtest=1.17.0               # TPL the Trilinos STK packages declare as required even with tests off (MiniEM dependency build)