[Metrics] Expose cached prompt tokens by cache tier

[cquil11]

Changes

• Adds vllm:prompt_tokens_cached_by_source_total{source=...}:
  • device: local accelerator prefix cache (HBM)
  • host: host-memory offload (DRAM/CPU)
  • disk: filesystem/NVMe offload.
  • p2p: direct engine-to-engine KV transfer.
  • external: external cache service or unresolved source.
• Accepts only these five source values. Uninstrumented connectors default to external.
• Preserves existing logical metrics. Source totals are intended to match vllm:prompt_tokens_cached_total.
• Connector mappings:
  • NIXL, Mooncake transfer, MoRIIO: p2p.
  • Mooncake Store: external.
  • Simple offload: host or disk.
  • Native offload: attributes each reused token range to the KV blocks actually selected for loading.
    • If all required blocks for a range come from one source, reports that source.
    • If the same range requires blocks from both host memory and disk, reports external for that range. This avoids counting the same tokens twice or guessing a split.
    • Separate token ranges can still report different sources, such as host for one range and disk for another.
• Preserves promotion origin per request. Truncates attribution after partial transfer failures.
• Initializes all five series at zero.
• Supports Python and Rust frontends. Rust requires rebuilding the binary. Older engine payloads fall back to external.

Closes vllm-project#53368.

Validation

DeepSeek-V4-Pro, 3,600-second AIPerf AgentX sweeps, evaluations disabled. AIPerf scraped Prometheus. Artifacts include JSON/CSV metrics and request logs.

• B200 — passed: DRAM c8, Simple NVMe c14, native DRAM+NVMe c14.
• GB300 — passed: NIXL 1P/1D c256.

Source counters reconciled with logical totals on every engine. GPU runs used the Python frontend. Rust was tested locally.

B200 included separate backend backports #55712 and #50014. P2P: 1,740 completed requests, zero request errors, 435 drain-deadline cancellations. Two Dynamo counter-reset warnings did not affect vLLM source reconciliation.

AI assistance disclosure

AI assistance was used for research, implementation, test authoring, and validation. This draft is intentionally opened for human line-by-line review before any upstream submission. The human submitter must understand and be able to defend the change end to end.

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