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GPU-accelerated batched inference for MACE, MatGL (TensorNet/M3GNet/CHGNet), and FairChem MLIPs using NValchemi, enabling parallel static, relax, and MD workflows across multiple structures simultaneously.
NValchemi Integration: Integrated NVIDIA's NValchemi toolkit into base wrapper dispatch for GPU-parallel batch static, relax (FIRE), and MD (NVT/NPT/NVE) runs.
Inflight batching: Implemented an evict-and-replace rolling GPU window (inflight batching) for FIRE relaxations to budget VRAM for very large structure sets.
Model Wrappers: Created custom NValchemi wrappers for MatGL (M3GNet/CHGNet) and FairChem (UMA). Fixed MACE multi-head indexing to select the correct selected head (e.g., omat_pbe = head 5) instead of defaulting to head 0.
Environments & CI: Upgraded mace-agent to Python 3.12 and added nvalchemi-toolkit dependencies to all MLIP conda environments.
Test Stability: Fixed import-time NameErrors on HostMemory in basic environments, resolved M3GNet/CHGNet test assertions, and automated wrong-environment test skips via class-scoped autouse pytest fixtures.