[Distributed] Add send and recv helpers #5719

andoorve · 2024-06-20T17:45:52Z

This adds send and recv helpers.

cc: @youkaichao @stephanie-wang @simon-mo

youkaichao · 2024-06-20T18:06:32Z

vllm/distributed/object_list_ops.py

+                                                _tensor_to_object)
+
+
+def send_object_list(object_list, dst, group=None, device=None):


to be honest, we never send object list literally. all we need is just send_object. can we add send_object to group coordinator, with the signature as broadcast_object? in the implementation, we can first send a int tensor with size 1 to send the size info, and then send serialized python object, finally send all tensors.

Hey @youkaichao it doesn't look like we actually have broadcast_object in group coordinator. We only support broadcast_object_list.

I think I kind of understand what you are saying, but will there be a big difference? I just tried to make it completely symmetric with broadcast* ops to avoid spending more time on it. Trying to see if I'm missing something

it's here #5399 . too many things recently, that i didn't find time to finish it :(

Ohhh got it - in that case can we keep doing send_object as part of that PR or a separate one? Just want to see if we can keep this PR simple as it's just symmetric with the current state of broadcast* for now.

I prefer we only keep send_object in this PR, in the future i want to deprecate broadcast_object_list, because it is confusing. list is also an object, right?

Got it. To be clear, you are not referring to using shm for this right? I think because #5399 does not do it this way:

in the implementation, we can first send a int tensor with size 1 to send the size info, and then send serialized python object, finally send all tensors.

It either uses shm or uses broadcast_object_list as a fallback

yeah, you don't need to use shm for this.

Made the change as per your comments

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

vllm/distributed/parallel_state.py

andoorve · 2024-06-20T20:25:16Z

The test failures here seem weird. They claim the commit does not exist but it does.

vllm/distributed/communication_op.py

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

vllm/distributed/parallel_state.py

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

youkaichao · 2024-06-22T02:03:50Z

vllm/distributed/parallel_state.py

+                                                       group)
+
+        # Send object size
+        torch.distributed.send(size_tensor, dst=dst, group=group)


our api uses relative rank inside the group, but pytorch uses global ranks:

src (int) – Source rank from which to broadcast object_list. Source rank is based on global process group (regardless of group argument)

Changed it so {send,recv}, {send,recv}_object, {send,recv}_tensor_dict. Also added new test for {send,recv}.

youkaichao · 2024-06-22T02:05:59Z

vllm/distributed/parallel_state.py

+    def send_object(self,
+                    obj: Any,
+                    dst: int,
+                    group: Optional[ProcessGroup] = None) -> None:


we know we are sending python object here, so it is reasonable to just use cpu_group.

youkaichao · 2024-06-22T02:06:15Z

vllm/distributed/parallel_state.py

+
+        current_device = _get_pg_default_device(group)
+        # Serialize object to tensor.
+        object_tensor, size_tensor = _object_to_tensor(obj, current_device,


safe to directly use "cpu" here.

youkaichao · 2024-06-22T02:06:43Z

vllm/distributed/parallel_state.py

+
+        current_device = _get_pg_default_device(group)
+        # Serialize object to tensor.
+        object_tensor, size_tensor = _object_to_tensor(obj, current_device,


safe to just use pickle.dumps and torch.frombuffer stuff.

Done these simplifications

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

youkaichao · 2024-06-22T03:05:08Z

vllm/distributed/parallel_state.py

+def get_pipeline_model_parallel_world_size():
+    """Return world size for the pipeline model parallel group."""
+    return get_pp_group().world_size
+
+
+def get_pipeline_model_parallel_rank():
+    """Return my rank for the pipeline model parallel group."""
+    return get_pp_group().rank_in_group
+


these two are not used

Do you mean they are not used currently? Planning to use them in next PRs

yes, they are not used. in the future i will remove legacy usage like get_tensor_model_parallel_rank, as pointed in #5293 (comment) . The basic idea is that, "users" of parallel_state can assemble the functionality they want, rather than keep adding new helper functions in parallel_state .

Understood, basically everything is done through GroupCoordinator. Removed all the extra helper functions.

youkaichao · 2024-06-22T03:06:24Z

vllm/distributed/parallel_state.py

+def is_pipeline_model_parallel_first_rank():
+    """Return True if the rank is the first rank in the
+    pipeline model parallel group."""
+    return get_pp_group().rank_in_group == 0
+
+
+def is_pipeline_model_parallel_last_rank():
+    """Return True if the rank is the last rank in the
+    pipeline model parallel group."""
+    return get_pp_group().rank_in_group == get_pp_group().world_size - 1
+
+


add them in the GroupCoordinator.is_first_rank, so that tp group might also use it as well in the future.

youkaichao

overall it looks good, left some nit comments

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

youkaichao

LGTM, thanks for addressing my comments!

youkaichao · 2024-06-22T03:19:47Z

tests/distributed/test_comm_ops.py

@@ -8,12 +8,13 @@
 import ray
 import torch

-from vllm.distributed import (broadcast_tensor_dict,
+from vllm.distributed import (broadcast_tensor_dict, get_pp_group,
+                              is_pipeline_model_parallel_first_rank,


nit: update the test

Thanks, forgot to rerun tests

Signed-off-by: Muralidhar Andoorveedu <[email protected]>

andoorve · 2024-06-23T19:16:02Z

Hey @youkaichao can this be merged? Test failure is unrelated here:


2024-06-22 15:11:43 PDT | E               Cannot access gated repo for url https://huggingface.co/meta-llama/Llama-2-7b-hf/resolve/main/config.json.
-- | --
  | 2024-06-22 15:11:43 PDT | E               Access to model meta-llama/Llama-2-7b-hf is restricted. You must be authenticated to access it.

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(vllm-project#5905) Signed-off-by: Xiaowei Jiang <[email protected]> Co-authored-by: Roger Wang <[email protected]> * [Bugfix][Hardware][Intel CPU] Fix unpassed multi_modal_kwargs for CPU runner (vllm-project#5956) * [Core] Registry for processing model inputs (vllm-project#5214) Co-authored-by: ywang96 <[email protected]> * Unmark fused_moe config json file as executable (vllm-project#5960) * [Hardware][Intel] OpenVINO vLLM backend (vllm-project#5379) * [Bugfix] Better error message for MLPSpeculator when `num_speculative_tokens` is set too high (vllm-project#5894) Signed-off-by: Thomas Parnell <[email protected]> * [CI/Build] [2/3] Reorganize entrypoints tests (vllm-project#5904) * [Distributed] Make it clear that % should not be in tensor dict keys. (vllm-project#5927) Signed-off-by: Xiaowei Jiang <[email protected]> * [Spec Decode] Introduce DraftModelRunner (vllm-project#5799) * [Bugfix] Fix compute datatype for cutlass 3.x epilogues (vllm-project#5931) * [ Misc ] Remove `fp8_shard_indexer` from Col/Row Parallel Linear (Simplify Weight Loading) (vllm-project#5928) Co-authored-by: Robert Shaw <rshaw@neuralmagic> * [ Bugfix ] Enabling Loading Models With Fused QKV/MLP on Disk with FP8 (vllm-project#5921) Co-authored-by: Robert Shaw <rshaw@neuralmagic> * Support Deepseek-V2 (vllm-project#4650) Co-authored-by: Philipp Moritz <[email protected]> * [Bugfix] Only add `Attention.kv_scale` if kv cache quantization is enabled (vllm-project#5936) * Unmark more files as executable (vllm-project#5962) * [Bugfix] Fix Engine Failing After Invalid Request - AsyncEngineDeadError (vllm-project#5963) Co-authored-by: Robert Shaw <rshaw@neuralmagic> * [Kernel] Flashinfer for prefill & decode, with Cudagraph support for decode (vllm-project#4628) Co-authored-by: LiuXiaoxuanPKU <[email protected]>, bong-furiosa <[email protected]> * [Bugfix][TPU] Fix TPU sampler output (vllm-project#5978) * [Bugfix][TPU] Fix pad slot id (vllm-project#5977) * [Bugfix] fix missing last itl in openai completions benchmark (vllm-project#5926) * [Misc] Extend vLLM Metrics logging API (vllm-project#5925) Co-authored-by: Antoni Baum <[email protected]> * [Kernel] Add punica dimensions for Granite 3b and 8b (vllm-project#5930) Signed-off-by: Joe Runde <[email protected]> * [Bugfix] Fix precisions in Gemma 1 (vllm-project#5913) * [Misc] Update Phi-3-Vision Example (vllm-project#5981) Co-authored-by: Cyrus Leung <[email protected]> * [Bugfix] Support `eos_token_id` from `config.json` (vllm-project#5954) * [Core] Optimize `SequenceStatus.is_finished` by switching to IntEnum (vllm-project#5974) * [Kernel] Raise an exception in MoE kernel if the batch size is larger then 65k (vllm-project#5939) * [ CI/Build ] Added E2E Test For Compressed Tensors (vllm-project#5839) Co-authored-by: Michael Goin <[email protected]> Co-authored-by: Robert Shaw <rshaw@neuralmagic> * [CI/Build] Add TP test for vision models (vllm-project#5892) * [ CI/Build ] LM Eval Harness Based CI Testing (vllm-project#5838) Co-authored-by: Robert Shaw <rshaw@neuralmagic> * [Bugfix][CI/Build][Hardware][AMD] Install matching torchvision to fix AMD tests (vllm-project#5949) * [CI/Build] Temporarily Remove Phi3-Vision from TP Test (vllm-project#5989) * [CI/Build] Reuse code for checking output consistency (vllm-project#5988) * [CI/Build] [3/3] Reorganize entrypoints tests (vllm-project#5966) * [ci][distributed] fix device count call [ci][distributed] fix some cuda init that makes it necessary to use spawn (vllm-project#5991) * [Frontend]: Support base64 embedding (vllm-project#5935) Co-authored-by: Cyrus Leung <[email protected]> * [Lora] Use safetensor keys instead of adapter_config.json to find unexpected modules. (vllm-project#5909) Co-authored-by: sang <[email protected]> * [ CI ] Temporarily Disable Large LM-Eval Tests (vllm-project#6005) Co-authored-by: [email protected] <rshaw@neuralmagic> * [Misc] Fix `get_min_capability` (vllm-project#5971) * [ Misc ] Refactor w8a8 to use `process_weights_after_load` (Simplify Weight Loading) (vllm-project#5940) Co-authored-by: Robert Shaw <rshaw@neuralmagic> * [misc][cuda] use nvml to avoid accidentally cuda initialization (vllm-project#6007) * [Speculative Decoding 2/2 ] Integrate typical acceptance sampler into Spec Decode Worker (vllm-project#5348) * Revert test changes * cleanup * llm engine cleanup * utils.py cleanup * custom ops refactor * move xops to ops * remove vllm/hpu/attn_bias.py * whitespace fix * revert accidental changes in rmsnorm * Fix hpugraph hashing * add trim_attn_metadata comment * fix prompt bucketing: * [ CI ] Re-enable Large Model LM Eval (vllm-project#6031) * [doc][misc] remove deprecated api server in doc (vllm-project#6037) * [Misc] update benchmark backend for scalellm (vllm-project#6018) * [doc][misc] further lower visibility of simple api server (vllm-project#6041) Co-authored-by: Simon Mo <[email protected]> * [Bugfix] Use RayActorError for older versions of Ray in RayTokenizerGroupPool (vllm-project#6039) * [Bugfix] adding chunking mechanism to fused_moe to handle large inputs (vllm-project#6029) * add FAQ doc under 'serving' (vllm-project#5946) * [Bugfix][Doc] Fix Doc Formatting (vllm-project#6048) * [Bugfix] Add explicit `end_forward` calls to flashinfer (vllm-project#6044) * [BugFix] Ensure worker model loop is always stopped at the right time (vllm-project#5987) * [Frontend] Relax api url assertion for openai benchmarking (vllm-project#6046) * [Model] Changes to MLPSpeculator to support tie_weights and input_scale (vllm-project#5965) Signed-off-by: Thomas Parnell <[email protected]> Co-authored-by: Joshua Rosenkranz <[email protected]> * [Core] Optimize block_manager_v2 vs block_manager_v1 (to make V2 default) (vllm-project#5602) * [Frontend] Add template related params to request (vllm-project#5709) * [VLM] Remove `image_input_type` from VLM config (vllm-project#5852) Signed-off-by: Xiaowei Jiang <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Roger Wang <[email protected]> * [Doc] Reinstate doc dependencies (vllm-project#6061) * guard model loader wa for hpu --------- Signed-off-by: Thomas Parnell <[email protected]> Signed-off-by: Lei Wen <[email protected]> Signed-off-by: Joe Runde <[email protected]> Signed-off-by: kevin <[email protected]> Signed-off-by: Rafael Vasquez <[email protected]> Signed-off-by: Stephanie Wang <[email protected]> Signed-off-by: Stephanie <[email protected]> Signed-off-by: Xiaowei Jiang <[email protected]> Signed-off-by: Joe Runde <[email protected]> Co-authored-by: Li, Jiang <[email protected]> Co-authored-by: Jianan Gu <[email protected]> Co-authored-by: Woosuk Kwon <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Tyler Michael Smith <[email protected]> Co-authored-by: Michael Goin <[email protected]> Co-authored-by: youkaichao <[email protected]> Co-authored-by: zifeitong <[email protected]> Co-authored-by: Robert Shaw <[email protected]> Co-authored-by: Cody Yu <[email protected]> Co-authored-by: Philipp Moritz <[email protected]> Co-authored-by: Antoni Baum <[email protected]> Co-authored-by: Jie Fu (傅杰) <[email protected]> Co-authored-by: Allen.Dou <[email protected]> Co-authored-by: Simon Mo <[email protected]> Co-authored-by: Kuntai Du <[email protected]> Co-authored-by: Dipika Sikka <[email protected]> Co-authored-by: Sanger Steel <[email protected]> Co-authored-by: Thomas Parnell <[email protected]> Co-authored-by: leiwen83 <[email protected]> Co-authored-by: Lei Wen <[email protected]> Co-authored-by: SangBin Cho <[email protected]> Co-authored-by: Alexander Matveev <[email protected]> Co-authored-by: Nick Hill <[email protected]> Co-authored-by: Amit Garg <[email protected]> Co-authored-by: Charles Riggins <[email protected]> Co-authored-by: Liqian Chen <[email protected]> Co-authored-by: zhyncs <[email protected]> Co-authored-by: Kunshang Ji <[email protected]> Co-authored-by: Abhilash Majumder <[email protected]> Co-authored-by: Abhilash Majumder <[email protected]> Co-authored-by: Bruce Fontaine <[email protected]> Co-authored-by: zifeitong <[email protected]> Co-authored-by: sroy745 <[email protected]> Co-authored-by: Isotr0py <[email protected]> Co-authored-by: Joe Runde <[email protected]> Co-authored-by: Chang Su <[email protected]> Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Kevin H. Luu <[email protected]> Co-authored-by: Ronen Schaffer <[email protected]> Co-authored-by: sergey-tinkoff <[email protected]> Co-authored-by: milo157 <[email protected]> Co-authored-by: Shukant Pal <[email protected]> Co-authored-by: Hongxia Yang <[email protected]> Co-authored-by: DearPlanet <[email protected]> Co-authored-by: Rafael Vasquez <[email protected]> Co-authored-by: Varun Sundar Rabindranath <[email protected]> Co-authored-by: Varun Sundar Rabindranath <[email protected]> Co-authored-by: Joshua Rosenkranz <[email protected]> Co-authored-by: Davis Wertheimer <[email protected]> Co-authored-by: Jinzhen Lin <[email protected]> Co-authored-by: Jee Li <[email protected]> Co-authored-by: rohithkrn <[email protected]> Co-authored-by: Murali Andoorveedu <[email protected]> Co-authored-by: Woo-Yeon Lee <[email protected]> Co-authored-by: Matt Wong <[email protected]> Co-authored-by: aws-patlange <[email protected]> Co-authored-by: Stephanie Wang <[email protected]> Co-authored-by: Stephanie <[email protected]> Co-authored-by: Luka Govedič <[email protected]> Co-authored-by: Chih-Chieh-Yang <[email protected]> Co-authored-by: Lucas Wilkinson <[email protected]> Co-authored-by: sasha0552 <[email protected]> Co-authored-by: Chip Kerchner <[email protected]> Co-authored-by: Abhinav Goyal <[email protected]> Co-authored-by: xwjiang2010 <[email protected]> Co-authored-by: Divakar Verma <[email protected]> Co-authored-by: Ilya Lavrenov <[email protected]> Co-authored-by: Robert Shaw <rshaw@neuralmagic> Co-authored-by: wangding zeng <[email protected]> Co-authored-by: Lily Liu <[email protected]> Co-authored-by: LiuXiaoxuanPKU <[email protected]>, bong-furiosa <[email protected]> Co-authored-by: mcalman <[email protected]> Co-authored-by: William Lin <[email protected]> Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: llmpros <[email protected]> Co-authored-by: sang <[email protected]> Co-authored-by: Avshalom Manevich <[email protected]> Co-authored-by: James Whedbee <[email protected]> Co-authored-by: Joshua Rosenkranz <[email protected]> Co-authored-by: danieljannai21 <[email protected]>

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Add send and recv helpers

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Fix comments

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andoorve force-pushed the pp-helpers branch from 0e55233 to ae4a17a Compare June 20, 2024 19:25

Change send and recv object to send and recv object_lists

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andoorve commented Jun 20, 2024

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Remove module level function

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Remove world size check and add assert for rank.

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Simplifications

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Streamed send/recv APIs with local ranks

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Refactor send and recv functions and add new test

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Add is_first_rank, is_last_rank, remove helper functions

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chore: Refactor send and recv functions for pynccl tests

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		_tensor_to_object)


		def send_object_list(object_list, dst, group=None, device=None):

[Distributed] Add send and recv helpers #5719

[Distributed] Add send and recv helpers #5719

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andoorve commented Jun 23, 2024

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