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Quantum ESPRESSO: Structured Data

We present in this page the structured representations for the Quantum ESPRESSO modeling application, and for its specific compute parameters.

Application

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{
    "schemaId": "software-directory-modeling-espresso", 
    "type": "object", 
    "$schema": "http://json-schema.org/draft-04/schema#", 
    "properties": {
        "version": {
            "enum": [
                "5.1.1", 
                "5.2.1", 
                "5.4.0", 
                "6.0.0"
            ]
        }, 
        "name": {
            "enum": [
                "espresso"
            ]
        }, 
        "summary": {
            "enum": [
                "Quantum Espresso"
            ]
        }
    }, 
    "title": "espresso app schema"
}

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{
    "shortName": "qe", 
    "version": "5.1.1", 
    "name": "espresso", 
    "summary": "Quantum Espresso"
}

Compute Parameters

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{
    "title": "quantum espresso arguments schema", 
    "schemaId": "software-directory-modeling-espresso-arguments", 
    "additionalProperties": false, 
    "$schema": "http://json-schema.org/draft-04/schema#", 
    "type": "object", 
    "properties": {
        "ntg": {
            "type": "integer", 
            "description": "In order to allow good parallelization of the 3D FFT when the number of processors exceeds the number of FFT planes, FFTs on Kohn-Sham states are redistributed to `task` groups so that each group can process several wavefunctions at the same time."
        }, 
        "ndiag": {
            "type": "integer", 
            "description": "A further level of parallelization, independent on PW or k-point parallelization, is the parallelization of subspace diagonalization / iterative orthonormalization. Both operations required the diagonalization of arrays whose dimension is the number of Kohn-Sham states (or a small multiple of it). All such arrays are distributed block-like across the `linear-algebra group`, a subgroup of the pool of processors, organized in a square 2D grid. As a consequence the number of processors in the linear-algebra group is given by n2, where n is an integer; n2 must be smaller than the number of processors in the PW group. The diagonalization is then performed in parallel using standard linear algebra operations."
        }, 
        "nimage": {
            "type": "integer", 
            "description": "Processors can be divided into different `images`, each corresponding to a different self-consistent or linear-response calculation, loosely coupled to others."
        }, 
        "npools": {
            "type": "integer", 
            "description": "Each image can be subpartitioned into `pools`, each taking care of a group of k-points."
        }, 
        "nband": {
            "type": "integer", 
            "description": "Each pool is subpartitioned into `band groups`, each taking care of a group of Kohn-Sham orbitals (also called bands, or wavefunctions)."
        }
    }
}

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{
    "ntg": 1, 
    "npools": 1, 
    "nband": 1
}