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[Speculative decoding] [Multi-Step] decouple should_modify_greedy_probs_inplace #6971

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merged 3 commits into from
Aug 9, 2024

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@SolitaryThinker SolitaryThinker commented Jul 31, 2024

Preparation PR for multi step. Not a blocker, but will make MS PR smaller and improve perf.

Decouple should_modify_greedy_probs_inplace from include_gpu_probs_tensor so that multi-step can set include_gpu_probs_tensor without also setting should_modify_greedy_probs_inplace and incurring the overhead of the probs modification (causes a GPU<>CPU sync). Not a blocker for multi-step, but does add ~1ms of GPU bubble between each step on A10G, will be a much bigger slow down on H100.

@cadedaniel This may be a perf bug for spec decode as well? I also can't seem to get spec_decode tests to all consistently pass locally?

Torch Profile with multi-step and without decoupling (should_modify_greedy_probs_inplace == True)
image

cc @WoosukKwon @zhuohan123 @Yard1 @comaniac @rkooo567


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@cadedaniel
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Will take a look tomorrow.

@SolitaryThinker SolitaryThinker mentioned this pull request Jul 31, 2024
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LGTM.

  • Can we add a test for this? e.g. something that runs include_gpu_probs_tensor but without modified greedy probs, and we verify that the gpu probs tensor is there but the greedy probs are not modified.
  • The modification of greedy probs should not incur a CPU sync 😄 . I'll take a look at that.

Comment on lines +290 to +299
(self.scorer_worker.model_runner.model.sampler.
should_modify_greedy_probs_inplace) = True
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Can we put this behind an interface so refactors to the worker / model / sampler do spread everywhere?

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Not sure if there is a clean way to do this, as the line above sets include_gpu_probs_tensor before this PR also change the decoupled (this PR) should_modify_greedy_probs_inplace. Seems the scorer worker is passed around as WorkerBase so would need to add change that class which is not ideal. Am I missing something?

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Oh right.. sorry I must have misread.

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cadedaniel commented Jul 31, 2024

By the way, what model is running in the profile ? pretty surprised by any CPU sync causing 17ms of overhead when the sampler already does a CPU sync at the beginning

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SolitaryThinker commented Jul 31, 2024

This is llama 8B on A10G, but the profile is with multi-step, which has removed all the other sources of CPU syncs (CPU prepare_input, GPU<>CPU transfer for sampled token, pythonization)

Comment on lines +290 to +299
(self.scorer_worker.model_runner.model.sampler.
should_modify_greedy_probs_inplace) = True
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Oh right.. sorry I must have misread.

@@ -1067,6 +1067,10 @@ def org_vocab_size(self):
def include_gpu_probs_tensor(self):
return self.base_layer.include_gpu_probs_tensor

@property
def should_modify_greedy_probs_inplace(self):
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Confused why this is here, why does this layer need it?

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I'm not sure, I just greped for all the places that include_gpu_probs_tensor was used and added the change there to keep semantics identical. See the lines above.

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Just added test for the inplace modification, let me know if there's anything else.

@comaniac comaniac enabled auto-merge (squash) August 9, 2024 04:31
@github-actions github-actions bot added the ready ONLY add when PR is ready to merge/full CI is needed label Aug 9, 2024
@comaniac comaniac merged commit 57b7be0 into vllm-project:main Aug 9, 2024
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sfc-gh-mkeralapura pushed a commit to sfc-gh-mkeralapura/vllm that referenced this pull request Aug 12, 2024
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