[KV Offload] Support packed HMA KV cache layout

[LucasWilkinson]

Summary

• add an opt-in VLLM_USE_PACKED_HMA_KV_CACHE path for multi-group HMA KV cache packing
• keep the existing DeepSeek V4 packed path unchanged
• register packed HMA offload as one canonical backing tensor with one full-row ref per KV group, preserving the packed topology for CPU offload

Duplicate-work check

• Checked open PRs for packed HMA KV cache, gpt-oss gemma packed kv cache, VLLM_USE_PACKED_HMA_KV_CACHE, packed KV cache offloading, and hybrid KV cache offload.
• Related work exists, especially [KV Connector] Canonical KV Cache Allocation for HMA Models #37885 and [KV Offload] Reshape the transfer data model: per group specs and offloaded side alignment offset #44865, but this PR is intentionally narrower: it is a flagged alternative to [KV Connector] Canonical KV Cache Allocation for HMA Models #37885 for gpt-oss/Gemma-style HMA packing and preserves [DSv4] Pack KV caches into contiguous per-block allocations for DeepSeek V4 #44577/DeepSeek V4 behavior.
• [DSv4] Pack KV caches into contiguous per-block allocations for DeepSeek V4 #44577 is merged and this PR builds on that packed layout support rather than duplicating the DSV4 change.

Benchmarks

• openai/gpt-oss-20b, B300, 128K, OffloadingConnector, 2 CPU-hit iterations: packed HMA full-row refs used 1 CPU tensor and averaged ~124.95 ms vs per-slice registration with 12 CPU tensors at ~144.37 ms (~13.5% faster).
• google/gemma-3-1b-it, 4K: packed HMA used 1 CPU tensor vs 4 and CPU-hit latency was effectively flat, ~12.23 ms vs ~12.32 ms.

Tests

• .venv/bin/python -m pytest tests/v1/core/test_contiguous_kv_packing.py tests/v1/simple_kv_offload/test_scheduler.py tests/v1/kv_connector/unit/offloading_connector/test_worker.py tests/v1/kv_offload/cpu/test_gpu_worker.py -q
• .venv/bin/pre-commit run ruff-check --files vllm/v1/kv_offload/base.py vllm/v1/kv_offload/cpu/gpu_worker.py vllm/distributed/kv_transfer/kv_connector/v1/offloading/worker.py
• commit hook also ran ruff check, ruff format, typos, mypy py3.10, SPDX, config validation, and other repository hooks successfully.

AI Assistance

AI assistance was used to implement and iterate on this change. This PR has been reviewed by the author.