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[perf] fix: fix npu profiling scripts#5226

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tongtong0613 wants to merge 1 commit intoverl-project:mainfrom
tongtong0613:prof-fix
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[perf] fix: fix npu profiling scripts#5226
tongtong0613 wants to merge 1 commit intoverl-project:mainfrom
tongtong0613:prof-fix

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What does this PR do?

fix npu profiling scripts

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Code Review

This pull request updates NPU profiling scripts by increasing gpu_memory_utilization and setting a large update_weights_bucket_megabytes. While these changes can improve performance, setting the weight update bucket size to 4GB in an example script is risky as it significantly increases memory pressure on the training worker and may lead to out-of-memory errors on hardware with less memory. I've added comments suggesting to add a warning about the high memory requirement to mitigate this risk for other users.

actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
actor_rollout_ref.rollout.n=4 \
actor_rollout_ref.rollout.enable_chunked_prefill=False \
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \
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high

Setting update_weights_bucket_megabytes to 4096MB allocates a 4GB buffer on the training worker's device. This large allocation, combined with memory for the model and optimizer, significantly increases the risk of out-of-memory (OOM) errors, especially on devices with less memory. While it can improve performance, this high value in an example script is risky. It would be beneficial to add a comment to warn users about the high memory requirement.

Suggested change
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \
# NOTE: A large bucket size (4GB) is used for weight updates to improve throughput.
# This may cause OOM on devices with less memory. Consider lowering if you encounter OOM errors.
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \

actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
actor_rollout_ref.rollout.n=4 \
actor_rollout_ref.rollout.enable_chunked_prefill=False \
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \
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high

Setting update_weights_bucket_megabytes to 4096MB allocates a 4GB buffer on the training worker's device. This large allocation, combined with memory for the model and optimizer, significantly increases the risk of out-of-memory (OOM) errors, especially on devices with less memory. While it can improve performance, this high value in an example script is risky. It would be beneficial to add a comment to warn users about the high memory requirement.

Suggested change
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \
# NOTE: A large bucket size (4GB) is used for weight updates to improve throughput.
# This may cause OOM on devices with less memory. Consider lowering if you encounter OOM errors.
actor_rollout_ref.rollout.checkpoint_engine.update_weights_bucket_megabytes=4096 \

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