[Refactor][EC Connector] Add backend extension points to ECCPUWorker - #54033
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This pull request has merge conflicts that must be resolved before it can be |
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Thanks for the work. Can you also check whether #53190 is simlar to this PR? |
Yes, part of the fix is similar. I can remove the duplicate part from my PR. Is that bugfix PR expected to be merged soon? |
Yes. It will be merged soon. |
Signed-off-by: Akine-Ko <2923601304@qq.com>
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Signed-off-by: Akine-Ko <2923601304@qq.com>
Signed-off-by: Akine-Ko <2923601304@qq.com>
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: Repository UI Review profile: CHILL Plan: Team Run ID: 📒 Files selected for processing (7)
Included review availability: Your plan provides up to 10 included reviews per hour; 9 remain after this review. WalkthroughThe change makes NIXL validation conditional, centralizes directional CPU transfer submission, adds a transfer-backend shutdown hook, and routes zero-token model steps through EC connector no-forward processing. ChangesEC connector flow
Estimated code review effort: 3 (Moderate) | ~25 minutes Merge Risk: ⚪ Minimal · up to No concrete merge-blocking risk remains in the reviewed changes. Sequence Diagram(s)sequenceDiagram
participant GPUModelRunner
participant ECConnectorModelRunnerMixin
participant ECTransfer
GPUModelRunner->>ECConnectorModelRunnerMixin: process zero-token output
ECConnectorModelRunnerMixin->>ECTransfer: poll transfers and start load caches
ECTransfer-->>ECConnectorModelRunnerMixin: return connector output and metadata
ECConnectorModelRunnerMixin-->>GPUModelRunner: return ModelRunnerOutput
Suggested reviewers: 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
Remove legacy Model Runner V1 metadata and no-forward handling, and restore the unconditional V2 guard. Assisted-by: OpenAI Codex Signed-off-by: Akine-Ko <2923601304@qq.com>
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/ci run |
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✅ @Akine-Ko, CI is now available for this PR.
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✅ Triggered Buildkite CI #87803 for commit |
…llm-project#54033) Signed-off-by: Akine-Ko <2923601304@qq.com> Signed-off-by: Jyotirmoy Roy <jyotirmoyroy649@gmail.com>
Purpose
ECCPUWorkerprovides the shared execution model for CPU-backed encoder-cache offloading. It owns the shared mmap layout, descriptor management, transfer batching, Event-based completion tracking, save reconstruction, load reconstruction, and worker metadata reporting.Device backends use the same lifecycle while supplying their platform-specific Host-memory registration and transfer operations.
This implementation supports the Ascend backend introduced by:
vllm-project/vllm-ascend#13894
Backend Extension Points
ECCPUWorkerexposes three backend extension points._pin_shared_regionPrepares the shared mmap region for device transfers.
The base implementation uses vLLM's standard Host-memory pinning path.
AscendECCPUWorkeruses this point to register the mmap as pinned Host memory through CANN._submit_transferSubmits a batch of transfer descriptors for H2D or D2H execution.
The base implementation dispatches through
swap_blocks_batch.AscendECCPUWorkerdispatches through the corresponding CANN batched-copy operation.ECCPUTransferDirectionidentifies the H2D or D2H direction passed to the backend implementation._shutdown_transfer_backendPerforms backend-specific shutdown after the common worker lifecycle has waited for tracked in-flight transfer Events.
Device backends use this point for platform synchronization, transfer-resource release, and pinned Host-memory unregistration. The common shutdown path then releases worker state and cleans up the shared region.
With these extension points, device workers inherit the upstream
save_caches,flush_saves,start_load_caches, completion reporting, buffer recycling, and shutdown lifecycle.Model Runner Support
ECCPUConnectorsupports Model Runner V2 only.Test Plan
CPU and mock regression
This coverage includes connector construction and role handling, the Model Runner V2 requirement, scheduler behavior, metadata handling, and shared-region lifecycle.
NVIDIA CUDA worker validation
The worker coverage verifies that both save and load paths delegate transfer submission through
_submit_transfer()with the correct direction, and that common shutdown invokes_shutdown_transfer_backend()before shared-region cleanup.CUDA VLM end-to-end validation