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Phase 7: Add RL-Kernel CI, benchmark matrix, and release rules #36

Description

@inaniloquentee

Background

Split from #6 Phase 7: CI, Benchmarks, and Release Rules.

This issue owns the release-quality test and reporting matrix for the RL-Kernel integration. Earlier phases add controls, metadata, audit, operator comparison, distributed contracts, and profiling; this issue turns those pieces into repeatable CI/benchmark gates and publication rules.

Scope

  • Add a CI matrix structure for RL-Kernel integration coverage, split by unit, CPU reference, GPU operator, distributed contract, and benchmark jobs.
  • Add or formalize CPU tests for diagnostic math, metadata validation, fallback decisions, report serialization, and A0-A5 report slices.
  • Add GPU operator test hooks for supported RL-Kernel backends without making RL-Kernel mandatory for native vime CI.
  • Add distributed test hooks for TP/SP/CP contracts, with skip/xfail behavior based on hardware availability and backend descriptors.
  • Add batch-invariance CI coverage for same-sample replay across batch size, padding/packing, active-mask density, dynamic sampling, and microbatch partitioning.
  • Add named A0-A5 grid slices using the same report/result path as local audit runs.
  • Add a scheduled benchmark matrix for representative vime workloads.
  • Add a report template that separates operator-level, actor-window, and full-step claims.
  • Define release rules for speedup claims and consistency claims, including audit, tolerance-based strict, and bitwise strict wording.

Non-Goals

Acceptance Criteria

  • CI can run native vime tests with RL-Kernel unavailable and still verify structured fallback behavior.
  • CPU-only jobs cover diagnostic math, metadata validation, provenance comparison, and report serialization.
  • GPU jobs are capability-gated and report skipped/unsupported cases explicitly rather than silently passing strict claims.
  • Distributed jobs cover TP/SP/CP contract surfaces when enough GPUs are available.
  • Batch-invariance and A0-A5 grid slices use the same result/report path as local audit runs.
  • Benchmark reports identify model/workload, hardware, world sizes, dtype, backend IDs, contract IDs, warmup/measurement windows, and runtime/build fingerprints.
  • Release templates separate operator-level, actor-window, and full-step metrics and state whether consistency is audit, tolerance-based strict, or bitwise strict.

Hardware / Execution Notes

  • Most CI/report plumbing can be developed and reviewed on CPU or a single-card machine.
  • GPU operator CI needs at least one CUDA GPU and an installed backend for backend-specific claims; otherwise it should report unsupported/skipped capability-gated cases.
  • Distributed TP/SP/CP CI needs multiple GPUs, with 2 GPUs enough for minimal TP/collective smoke tests and 4-8 GPUs preferred for representative distributed contract coverage.
  • Scheduled full-step benchmarks need the target training/rollout cluster configuration; Blackwell/B-card hardware is only required for Blackwell-specific release claims.

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    consistencyRollout-training consistencyphase-7Phase 7 workstreamrl-kernelRL-Kernel integrationtelemetryStructured telemetry and observability

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