[TRTLLM-12440][feat] Add GMS-only weight sharing support

[chienchunhung]

@coderabbitai summary

Summary

Adds LoadFormat.GMS so multiple TRT-LLM instances on the same node can zero-copy share model weights via the GPU Memory Service (GMS) pool. The first instance loads weights as the writer (RW); subsequent peers materialize them read-only (RO) without disk I/O or per-instance copies.

Scope

In scope:

• LoadFormat.GMS enum value and nested GmsConfig (socket_path, mode, tag) on TorchLlmArgs.
• New GMSBackend adapter under tensorrt_llm/_torch/memory/, lazily imported only when GMS is selected.
• ModelLoader GMS branch with explicit RW / RO / unexpected-state handling, plus a guard that refuses to commit an unpopulated model to the pool.
• Cleanup hook released via PyTorchModelEngine.__del__.

Adjacent (sub-PR, ~15 lines): remove the redundant MXCheckpointLoader.p2p_succeeded property; is_weights_preloaded() (the abstract hook from BaseCheckpointLoader) is now the single accessor. Tests updated accordingly.

Out of scope:

• Networking and MX integration (the MX checkpoint format already merged in [TRTLLM-11851][feat] Add MX-only P2P checkpoint loading support for TRTLLM #13531 composes orthogonally with LoadFormat.GMS).
• Packaging the gpu_memory_service dependency. Same OSS-allowlist concern as MX; users install it manually for now.

Test Coverage

New unit test files (mock-based, CPU CI):

• tests/unittest/llmapi/test_gms_args.py — GmsConfig validation and LoadFormat.GMS Pydantic surface.
• tests/unittest/_torch/memory/test_gms_backend.py — GMSBackend lifecycle and helpers.
• tests/unittest/_torch/pyexecutor/test_model_loader_gms.py — ModelLoader GMS RW / RO / failure / edge-case branches.

Updated:

• tests/unittest/_torch/models/checkpoints/mx/test_mx_checkpoint_loader.py — six call sites switched to is_weights_preloaded() after removing the redundant p2p_succeeded property.

PR Checklist

Please review the following before submitting your PR:

• PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.

• PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

• Test cases are provided for new code paths (see test instructions)

• Any new dependencies have been scanned for license and vulnerabilities

• CODEOWNERS updated if ownership changes

• Documentation updated as needed

• Update tava architecture diagram if there is a significant design change in PR.

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• Please check this after reviewing the above items as appropriate for this PR.

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[chienchunhung]

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[tensorrt-cicd]

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