ML MCONF: Difference between revisions
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{{TAGDEF| | {{TAGDEF|ML_MCONF|[integer]|1500}} | ||
Description: This flag sets the maximum number of structures used for training in the machine learning force field method. | Description: This flag sets the maximum number of structures used for training in the machine learning force field method. | ||
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The default value is usually a safe value but should be set to a higher value as soon as it is reached. When this happens the code stops and gives an error instructing to increase {{TAG| | The default value is usually a safe value but should be set to a higher value as soon as it is reached. When this happens the code stops and gives an error instructing to increase {{TAG|ML_MCONF}}. | ||
This flag sets alse the maximum number of rows for the design matrix, which is usually a huge matrix. The design matrix is to be allocated statically at the beginning of the program, since several parts of the code use MPI shared memory and dynamic reallocation of these arrays can cause severe problems on some systems. So most of the main arrays are statically allocated in the code. An estimate of the design matrix and all other large arrays is printed out to the {{TAG|ML_LOGFILE}} before allocation. The design matrix is fully distributed in a block cyclic fashion for scaLAPACK and should almost perfectly linearly scale with the number of used processors. | This flag sets alse the maximum number of rows for the design matrix, which is usually a huge matrix. The design matrix is to be allocated statically at the beginning of the program, since several parts of the code use MPI shared memory and dynamic reallocation of these arrays can cause severe problems on some systems. So most of the main arrays are statically allocated in the code. An estimate of the design matrix and all other large arrays is printed out to the {{TAG|ML_LOGFILE}} before allocation. The design matrix is fully distributed in a block cyclic fashion for scaLAPACK and should almost perfectly linearly scale with the number of used processors. | ||
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{{sc|ML_FF_MCONF|Examples|Examples that use this tag}} | {{sc|ML_FF_MCONF|Examples|Examples that use this tag}} | ||
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{{TAG| | {{TAG|ML_LMLFF}}, {{TAG|ML_MCONF_NEW}}, {{TAG|ML_MB}} | ||
[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | ||
Revision as of 08:59, 23 August 2021
ML_MCONF = [integer]
Default: ML_MCONF = 1500
Description: This flag sets the maximum number of structures used for training in the machine learning force field method.
The default value is usually a safe value but should be set to a higher value as soon as it is reached. When this happens the code stops and gives an error instructing to increase ML_MCONF. This flag sets alse the maximum number of rows for the design matrix, which is usually a huge matrix. The design matrix is to be allocated statically at the beginning of the program, since several parts of the code use MPI shared memory and dynamic reallocation of these arrays can cause severe problems on some systems. So most of the main arrays are statically allocated in the code. An estimate of the design matrix and all other large arrays is printed out to the ML_LOGFILE before allocation. The design matrix is fully distributed in a block cyclic fashion for scaLAPACK and should almost perfectly linearly scale with the number of used processors.