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Feature/single node check #500
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rfhaque
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Dec 14, 2024
@rfhaque what is the status of this PR? How does it currently work? What docs would you need to add? When you want to run strong or weak scaling, do you need to explicitly disable the single-node test because only one variant is possible at a time? If that is the case, we need to document it well. |
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Description
This PR adds a check for the single node experiment- The single_node variant [default=True] ONLY asserts that the given experiment must run on 1 node- This check is enforced in thedetermine_allocation
method of the allocation modifier. If single node is enabled and the experiment requires/requests more than 1 node, the ramble setup throws an error- strong/weak scaling modes are decoupled from the single node mode (it's possible to scale on a single node)- An experiment trying to run on more than one node must explicitly specify~single_node
Take 2:
max_node_limit
to the system specs (lib/benchpark/system.py
) which is the max number of nodes allowed for an experiment on that system instantiation. Default value 1, value of 0 means no limitslib/benchpark/experiment.py
), we add a filter clause'{n_nodes} > 0 and {n_nodes} <= {max_node_limit}'
.max_node_limit
nodes duringramble setup
. Currently, it's not an error if zero experiments satisfy themax_node_limit
Dependencies: FIXME:Add a list of any dependencies.
(Potentially) Fixes #492
Type of Change
Checklist:
If adding/modifying a system:
system.py
file.github/workflows
If adding/modifying a benchpark:
application.py
and (maybe)package.py
under a new directoryfor this benchmark
section
If adding/modifying a experiment:
experiment.py
under existing directory for specific benchmarkIf adding/modifying core functionality:
.github/workflows
and.gitlab/ci
unit tests (if needed)