add parallelism for workflow (deepmodeling#222)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Introduced a new `parallelism` option in the workflow submission
process, allowing users to specify the parallelism level for their
workflows. This provides greater control over the execution parallelism,
enhancing efficiency and resource management.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: zjgemi <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Han Wang <[email protected]>

dpgen2/entrypoint/args.py

@@ -509,6 +509,7 @@ def submit_args(default_step_config=normalize_step_dict({})):
     doc_explore = "The configuration for exploration"
     doc_fp = "The configuration for FP"
     doc_name = "The workflow name, 'dpgen' for default"
+    doc_parallelism = "The parallelism for the workflow. Accept an int that stands for the maximum number of running pods for the workflow. None for default"
 
     return (
         dflow_conf_args()
@@ -552,6 +553,9 @@ def submit_args(default_step_config=normalize_step_dict({})):
             ),
             Argument("fp", dict, [], [variant_fp()], optional=False, doc=doc_fp),
             Argument("name", str, optional=True, default="dpgen", doc=doc_name),
+            Argument(
+                "parallelism", int, optional=True, default=None, doc=doc_parallelism
+            ),
         ]
     )
 

dpgen2/entrypoint/submit.py

@@ -749,7 +749,7 @@ def submit_concurrent_learning(
         # wf_config["inputs"]["do_finetune"] = False
         # finetune will not be done again if the old process is reused.
 
-    wf = Workflow(name=wf_config["name"])
+    wf = Workflow(name=wf_config["name"], parallelism=wf_config["parallelism"])
 
     if wf_config["inputs"].get("do_finetune", False):
         assert finetune_step is not None