Files
neuron-tai/.scratch/distributed-inference-performance/issues/01-baseline-profiling-harness.md
2026-07-14 16:55:52 +03:00

27 lines
1.1 KiB
Markdown

Status: done (2026-07-14)
# 01 — Baseline and profiling harness
## What to build
Create a deterministic stub-backed benchmark for a Route Session that measures
prefill and cached decode across direct and relay paths. Attribute time to model
execution, activation encoding/decoding, compression, connection setup, relay
queueing, local HTTP forwarding, and end-to-end seam latency. Record payload
sizes and connection counts without requiring a real model or external host.
## Acceptance criteria
- [x] The harness runs a fixed prompt and fixed generated-token count through a
two-node route in direct and relay modes.
- [x] It reports p50/p95 per-token latency, per-hop latency, payload bytes,
compression ratio, connection attempts, and queue wait.
- [x] It distinguishes prefill from decode and cached from stateless mode.
- [x] It emits machine-readable JSON suitable for CI artifacts and a concise
human-readable summary.
- [x] A test fixture can assert connection attempts and output token identity.
## Blocked by
None - completed. Verified with `PYTHONPATH=packages/node pytest -q tests/test_route_session_benchmark.py` (7 passed).