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Three logically distinct changes, bundled for atomic test green:
1. **P3c — prefill_long tile-granular Ring KV** (ADR-0060 §5.5.1 amendment).
Convert the ring from slice-granular (one full ``(d_head, S_local)``
KV slice per step) to tile-granular (``n_tiles`` tiles of
``TILE_S_KV`` per step). Nested loop with outer tile, inner ring step:
each tile propagates through all C ring positions before the next
tile starts, so IPCQ in-flight depth stays at 1 per direction.
Bootstrap at ``(t=0, k=0)`` outside the scratch_scope establishes the
persistent ``(m, ℓ, O)``; every other iteration scope-wraps + persists
via ``copy_to``. Per-rank persistent scratch shrinks to ~1 KB; per-tile
scope bounded by TILE_S_KV regardless of S_local. Headline:
prefill_long now completes at S_kv=128K (previously overflowed).
New: ``tests/attention/test_gqa_prefill_long_tile_ring.py``
(3 tests — ceiling-lift + tile-granular ipcq_copy count +
per-CUBE distributed output regression guard).
2. **Rename ``gqa_*`` → ``gqa_attention_*``** across kernel files,
function names, and importers. The "attention" name makes the role
explicit (GQA is grouped-query attention) and matches upstream Triton
FlashAttention naming conventions. Renames:
_gqa_decode_long.py -> _gqa_attention_decode_long.py
_gqa_decode_short.py -> _gqa_attention_decode_short.py
_gqa_prefill_long.py -> _gqa_attention_prefill_long.py
_gqa_prefill_short.py -> _gqa_attention_prefill_short.py
And function names ``gqa_<phase>_<context>_kernel`` →
``gqa_attention_<phase>_<context>_kernel``. Updated 1 bench file
(milestone_gqa_headline.py) and 10 test files.
3. **ADR-0060 / 0062 / 0063 / 0064: Proposed → Accepted**.
All four are reflected in production code and covered by tests:
- ADR-0060 (GQA fused attention): 4 kernels deployed; §5.5.1
amendment added for the tile-granular Ring KV introduced by P3c
(EN + KO mirror).
- ADR-0062 (lazy tl.load): LoadFuture + _await_pending live in
tl_context.py.
- ADR-0063 (tl.scratch_scope + tl.copy_to): used in every chain
reduce + tile sweep + ring step. EN-only previously; KO
translation authored as part of this commit (CLAUDE.md
bidirectional rule).
- ADR-0064 (per-op-type CPU issue cost): cpu_issue_cost.py +
issue_cost_table wiring in tl_context.py (Phase E).
Files git mv'd from docs/adr-proposed/ to docs/adr/ (EN) and
docs/adr-ko/ (KO). ADR-0061 (tl.broadcast) stays Proposed — no
implementation; documented as optional convenience primitive in
the ADR itself.
Tests: 88/88 focused regression green
(tests/attention/ + Phase E + TL discipline).
ADR pair verification: ``python tools/verify_adr_lang_pairs.py`` OK.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
163 lines
6.5 KiB
Python
163 lines
6.5 KiB
Python
"""Phase 1 spec test for P3c: tile-granular Ring KV in prefill_long
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(ADR-0060 §5.5 amendment + ADR-0063 §A.2).
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Today's prefill_long ring sends and receives full ``(d_head, S_local)``
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KV slices per step. Step 0's local-attention intermediates also live
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outside any ``scratch_scope`` (they're loaded as full-slice ``Kc``,
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``Vc`` and feed ``scores``, ``exp_scores`` as persistent allocations).
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At larger ``S_local`` both the step-0 leak and the ring step's
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in-scope intermediates grow linearly with ``S_local``, and at
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``S_local = 32K`` (S_kv=128K, C=4, T_q=4) the peak overflows the
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1 MiB pool.
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P3c converts the ring to **tile-granular**: a nested loop
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``for k in range(C): for t in range(n_tiles): ...`` where each
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iteration sends/recvs one ``(d_head, TILE_S_KV)`` tile (and its V
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counterpart). The persistent state shrinks to ``(m, ℓ, O)`` only
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(~1 KB); per-tile in-scope scratch is bounded by
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``TILE_S_KV`` regardless of ``S_local``. Ceiling lifted.
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Trade-off: the per-CUBE send count grows from ``2·(C-1)`` to
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``2·n_tiles·(C-1)``. At ``n_tiles=1`` (small ``S_local``) the count is
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unchanged, so the existing ``test_prefill_ring_c_*`` tests at
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``S_kv ∈ {16, 32}`` still pass.
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Phase 1 (this commit): tests only — production code lands in Phase 2.
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T1 fails today with a ``TLContext scratch overflow``; T2 fails today
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with the slice-granular ipcq_copy count; T5 passes today and is a
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regression guard for the per-CUBE output write count.
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"""
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from __future__ import annotations
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from pathlib import Path
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from kernbench.benches._gqa_attention_prefill_long import gqa_attention_prefill_long_kernel # noqa: F401
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from kernbench.ccl.install import load_ccl_config, resolve_algorithm_config
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from kernbench.ccl.sfr_config import configure_sfr_intercube_ring
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from kernbench.policy.placement.dp import DPPolicy
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from kernbench.runtime_api.bench_runner import run_bench
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from kernbench.runtime_api.types import resolve_device
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from kernbench.sim_engine.engine import GraphEngine
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from kernbench.topology.builder import resolve_topology
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TOPOLOGY_DEFAULT = Path(__file__).resolve().parents[2] / "topology.yaml"
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D_HEAD = 64
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DTYPE = "f16"
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def _ccl_cfg():
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return resolve_algorithm_config(
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load_ccl_config(), name="lrab_hierarchical_allreduce",
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)
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def _engine_factory(t, d):
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return GraphEngine(getattr(t, "topology_obj", t), enable_data=True)
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def _count(op_log, name: str) -> int:
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return sum(1 for r in op_log if r.op_name == name)
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def _run_prefill_ring(*, T_q: int, S_kv: int, C: int):
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"""Head-parallel prefill with Ring KV across C CUBEs."""
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topo = resolve_topology(str(TOPOLOGY_DEFAULT))
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def _bench_fn(ctx):
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configure_sfr_intercube_ring(
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ctx.engine, ctx.spec, _ccl_cfg(), ring_size=C,
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)
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dp_q = DPPolicy(cube="replicate", pe="replicate",
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num_cubes=C, num_pes=1)
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dp_kv = DPPolicy(cube="row_wise" if C > 1 else "replicate",
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pe="replicate", num_cubes=C, num_pes=1)
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dp_o = DPPolicy(cube="row_wise" if C > 1 else "replicate",
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pe="replicate", num_cubes=C, num_pes=1)
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q = ctx.zeros((T_q, D_HEAD), dtype=DTYPE, dp=dp_q,
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name=f"q_tlr_t{T_q}_c{C}_s{S_kv}")
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k = ctx.zeros((S_kv, D_HEAD), dtype=DTYPE, dp=dp_kv,
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name=f"k_tlr_t{T_q}_c{C}_s{S_kv}")
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v = ctx.zeros((S_kv, D_HEAD), dtype=DTYPE, dp=dp_kv,
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name=f"v_tlr_t{T_q}_c{C}_s{S_kv}")
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o = ctx.empty((T_q * C, D_HEAD), dtype=DTYPE, dp=dp_o,
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name=f"o_tlr_t{T_q}_c{C}_s{S_kv}")
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ctx.launch(
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f"gqa_prefill_long_tile_ring_t{T_q}_c{C}_s{S_kv}",
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gqa_attention_prefill_long_kernel,
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q, k, v, o,
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T_q, S_kv, D_HEAD, C,
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_auto_dim_remap=False,
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)
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return run_bench(
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topology=topo, bench_fn=_bench_fn,
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device=resolve_device(None),
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engine_factory=_engine_factory,
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)
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# ── T1: 128K ceiling lift ────────────────────────────────────────────
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def test_prefill_long_context_128k_completes():
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"""ADR-0063 §A.2 headline ceiling lift. At S_kv=128K with C=4,
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S_local=32K. Today: step-0 score-stack (~768 KB persistent) + ring
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scope (~768 KB) → 1.5 MB peak → TLContext scratch overflow. After
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P3c the persistent state is just ``(m, ℓ, O)`` (≈ 1 KB) and the
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per-tile in-scope scratch is bounded by TILE_S_KV.
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"""
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result = _run_prefill_ring(T_q=4, S_kv=131_072, C=4)
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assert result.completion.ok, (
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f"prefill_long at S_kv=128K must complete after tile-granular "
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f"ring lands; got {result.completion}"
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)
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# ── T2: tile-granular ipcq_copy count ────────────────────────────────
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def test_prefill_long_tile_granular_ipcq_count():
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"""ADR-0060 §5.5 amendment: with tile-granular sends, the per-CUBE
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send count grows from ``2·(C-1)`` to ``2·n_tiles·(C-1)``. Aggregated
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across all C CUBEs the total ipcq_copy becomes
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``2·n_tiles·(C-1)·C``.
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Config: T_q=4, S_kv=4096, C=2 → S_local=2048, n_tiles=2 (with
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TILE_S_KV=1024). Today: slice-granular total =
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``(C-1)·2·C = 4``. After P3c: tile-granular total =
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``(C-1)·n_tiles·2·C = 8``.
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"""
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C = 2
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n_tiles = 2 # S_local=2048 / TILE_S_KV=1024
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result = _run_prefill_ring(T_q=4, S_kv=4096, C=C)
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assert result.completion.ok, (
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f"prefill_long multi-tile ring must complete; got {result.completion}"
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)
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n_copy = _count(result.engine.op_log, "ipcq_copy")
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expected = (C - 1) * n_tiles * 2 * C
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assert n_copy == expected, (
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f"tile-granular ring: expected {expected} ipcq_copy "
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f"((C-1)·n_tiles·2·C = {C - 1}·{n_tiles}·2·{C}); got {n_copy}"
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)
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# ── T5: per-CUBE distributed output unchanged (regression guard) ─────
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def test_prefill_long_tile_ring_dma_write_count():
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"""ADR-0060 §5.5: per-CUBE distributed output must hold under the
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tile-granular ring rewrite. Each CUBE still writes its own head's
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output (no inter-CUBE reduce); dma_write_count == C.
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Today passes; must continue to pass after P3c.
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"""
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C = 4
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result = _run_prefill_ring(T_q=4, S_kv=4096, C=C)
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assert result.completion.ok
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n_writes = _count(result.engine.op_log, "dma_write")
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assert n_writes == C, (
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f"per-CUBE distributed output: expected {C} dma_writes (one per "
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f"CUBE); got {n_writes}"
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)
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