SEAMM Interaction EDA Plug-in

A SEAMM plug-in for Interaction EDA

• Free software: BSD-3-Clause

• Documentation: https://molssi-seamm.github.io/interaction_eda_step/index.html

• Code: https://github.com/molssi-seamm/interaction_eda_step

History

2026.11.9.2 – Psi4 as the EDA code, on CPUs

• The Interaction EDA step now offers Psi4 as well as GPU4PySCF. Psi4 runs the same second-generation ALMO-EDA on CPUs, with the Psi4 step’s environment (psi4.ini), for GGA and hybrid functionals such as ωB97X-V and for Hartree-Fock. Meta-GGAs such as ωB97M-V are not offered with Psi4, because it has no response kernel for them. With density fitting it agrees with GPU4PySCF to 0.021 kJ/mol or better per term for pairs.

• eda.json and eda.extxyz now record the structure’s system and configuration names, so results can be matched to their input.

• The Psi4 driver now keeps its density-fitted integrals in memory only when they fit: for a range-separated functional, about three tensors of 8 × N_aux × N² bytes. Before, a large cluster could stop with “not enough memory to do in-core” when it should have read them from disk.

• The user guide gives the measured times, the cores worth using and the memory needed with Psi4.

2026.11.9.1 – Fine integration grids for GPU4PySCF by default

• GPU4PySCF’s standard grids, (99,590) for the exchange-correlation and (50,194) for VV10 with pruning, are not converged for compact clusters: for Na⁺(H₂O)₆ they put 0.43 kJ/mol into the frozen term and 0.33 kJ/mol into dispersion, compared with Psi4 at the same nominal grids. The new “Integration grid” setting defaults to “fine”, (150,974) and (99,590), which agrees with Psi4 to 0.012 kJ/mol for the whole cluster. Pairs change by about 0.001 kJ/mol.

• “standard” keeps the earlier grids, about 7 times faster for a cluster, e.g. to match labels made with 2026.11.9 or earlier. The EDA method string now records the grids.

2026.11.9 – Psi4 backend: half the memory for density fitting, and memory from the allocation

• The Psi4 backend (not yet offered by the step) held two sets of density-fitted integrals at once: its EDA engine’s and those of the final SCF of the whole system. The SCF now runs first, and Psi4 frees its integrals before the engine builds its own, so only one set is in memory (a 1121-function cluster peaked at 141 GB with two). The terms are unchanged (to 1e-6 kJ/mol).

• When the integrals would not fit in memory, density fitting falls back to reading them from the scratch disk at each build (DISK_DF), slower but bounded.

• The step gives Psi4 80 % of the calculation’s memory; it ran with Psi4’s default of 4 GB before.

2026.11.8.1 – Internal: the Psi4 EDA driver’s integrals

• The Psi4 backend (not yet offered by the step) computes its integrals directly instead of keeping them in memory, which was 4.5 times slower for the EDA’s many Fock builds (HF Li+-EC: 260 s against 1179 s on 16 cores, the same terms), and its density-fitted path, which stopped at once, now works: the fitting basis is built explicitly. Density fitting is about 6-9 times faster, with terms within 0.03-0.06 kJ/mol of exact integrals.

2026.11.8 – The SAPT-comparable Pauli term in the extxyz, and where each EDA ran

• eda.extxyz now has EDA_ALMOEDA2_mod_pauli, the SAPT-comparable Pauli repulsion (Q-Chem’s MOD PAULI: frozen - classical electrostatic - dispersion), with its many-body parts, beside the orthogonal pauli. It and classical_electrostatic are the pair to compare with SAPT.

• Each frame and calculation records where it ran (EDA_platform: GPU, CUDA, driver and library versions).

• The calculations use the number of cores SEAMM’s ncores option allows.

2026.11.7 – First release: interaction energy decomposition with ALMO-EDA2 on GPUs

• A new step, Interaction EDA, that decomposes the interactions between the molecules of a structure into electrostatics, Pauli repulsion, dispersion, polarization and charge transfer, using second-generation ALMO-EDA in GPU4PySCF on an NVIDIA GPU.

• It computes the whole cluster and every pair, and optionally the triples within a distance, and gives each term’s 2-body, exact ≥3-body and (with triples) 3-body parts. Fragments are the molecules, with ion charges from their formal charges or a built-in catalog, or are given by an atom column.

• Each term is printed, stored as results and properties, and written per set of fragments to eda.extxyz and eda.json. The common electrostatics and Pauli terms are the pair comparable with SAPT; the native ALMO-EDA2 terms are kept as well.

• The defaults are the validated settings: ωB97M-V/def2-TZVPD with exact integrals and coupled FERF response (singular-value threshold 10⁻⁴). Validated to better than 10⁻⁵ kJ/mol against standalone GPU4PySCF runs on A30 and A100 GPUs, for cations, anions and neutral molecules.

• The installer creates the GPU4PySCF conda environment for the machine’s CUDA driver and checks that it can use the GPU. The step refuses to run on GPUs with little double-precision throughput (T4, L4, L40S …) unless told to allow them.

• A rerun computes only the calculations that are missing.