ML NCSHMEM: Difference between revisions

Latest revision as of 09:36, 5 February 2026

ML_NCSHMEM = [integer]
Default: ML_NCSHMEM = Number of available ranks per computational node

Description: Specifies the number of MPI ranks that share a single shared memory segment.

The total number of memory segments created equals the number of cores per node divided by ML_NCSHMEM. All memory segments have identical sizes, so a larger number of segments results in higher total memory consumption.

However, on systems with multiple NUMA domains, performance can degrade significantly during machine-learned force field inference if all domains access the same memory segment. For optimal performance, each NUMA domain should have its own dedicated shared memory segment. For more details, we refer to NCSHMEM.

@@ Line 1: / Line 1: @@
 {{DISPLAYTITLE:ML_NCSHMEM}}
-{{TAGDEF|ML_NCSHMEM|[integer]}}
+{{TAGDEF|ML_NCSHMEM|[integer]|Number of available ranks per computational node}}
-{{TAGDEF|ML_NCSHMEM|[integer]|Number of available ranks per node}}
-Description: Sets the number of ranks that share a shared memory segment.
+Description: Specifies the number of MPI ranks that share a single shared memory segment.
 ----
+The total number of memory segments created equals the number of cores per node divided by {{TAG|ML_NCSHMEM}}. All memory segments have identical sizes, so a larger number of segments results in higher total memory consumption.
+However, on systems with multiple NUMA domains, performance can degrade significantly during machine-learned force field inference if all domains access the same memory segment. For optimal performance, each NUMA domain should have its own dedicated shared memory segment. For more details, we refer to {{TAG|NCSHMEM}}.
 == Related tags and articles ==
-{{TAG|ML_LMLFF}}, {{TAG|ML_MODE}}, [[https://vasp.at/wiki/Shared_memory|shared memory]]
+{{TAG|ML_LMLFF}}, {{TAG|ML_MODE}}, {{TAG|NCSHMEM}}, [[Shared memory]]
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 [[Category:INCAR tag]][[Category:Machine-learned force fields]]