kernbench2/tests/attention/test_gqa_long_context.py

"""Phase 1 spec test for Phase C: long-context regression for the GQA
kernels (ADR-0060 §B "long/short context split" + ADR-0063 §A.2).

The headline panel today caps prefill at S_kv=16 / decode at S_kv≤128 —
NOT because the algorithm fails, but because the bump allocator never
recycles. ADR-0063 §A.2 (test req 3) requires a sweep at an S that
would overflow 1 MiB without recycling to complete after scope
discipline lands.

Scratch-budget estimate at C=4, P=8 (current 1 MiB pool):
  decode:  per-rank S_local = S_kv / 32; intermediates ≲ 500 KB at
           S_kv=32K (fits today — used as regression guard).
  prefill: per-rank S_local = S_kv / 4; ~16·S_local bytes per ring
           step × 4 steps ≈ 64·S_local bytes. Overflows at
           ~64 K tokens (64 × 16K > 1 MiB).

Phase 1 (this commit): tests only — production code lands in Phase 2.
The prefill test fails today with a RuntimeError("TLContext scratch
overflow"). After Phase 2 (scratch_scope + copy_to discipline) it
completes.
"""
from __future__ import annotations

from pathlib import Path

from kernbench.benches._gqa_attention_decode_long import gqa_attention_decode_long_kernel  # noqa: F401
from kernbench.benches._gqa_attention_prefill_long import gqa_attention_prefill_long_kernel  # noqa: F401
from kernbench.ccl.install import load_ccl_config, resolve_algorithm_config
from kernbench.ccl.sfr_config import (
    configure_sfr_intercube_multisip,
    configure_sfr_intercube_ring,
)
from kernbench.policy.placement.dp import DPPolicy
from kernbench.runtime_api.bench_runner import run_bench
from kernbench.runtime_api.types import resolve_device
from kernbench.sim_engine.engine import GraphEngine
from kernbench.topology.builder import resolve_topology

TOPOLOGY_DEFAULT = Path(__file__).resolve().parents[2] / "topology.yaml"

D_HEAD = 64
DTYPE = "f16"


def _ccl_cfg():
    return resolve_algorithm_config(
        load_ccl_config(), name="lrab_hierarchical_allreduce",
    )


def _engine_factory(t, d):
    return GraphEngine(getattr(t, "topology_obj", t), enable_data=True)


# ── Decode at moderate-long context (regression guard) ───────────────


def test_decode_long_context_32k_completes():
    """Decode at S_kv=32K (C=1, P=8) — per-rank S_local=4K. Should
    complete with current scratch usage (~few KB intermediates) and
    must continue to complete after the rewrite.

    This is a regression guard: scratch discipline shouldn't break
    decode's existing long-context capability.
    """
    topo = resolve_topology(str(TOPOLOGY_DEFAULT))

    def _bench_fn(ctx):
        configure_sfr_intercube_multisip(ctx.engine, ctx.spec, _ccl_cfg())
        P = 8
        S_kv = 32_768
        dp_full = DPPolicy(cube="replicate", pe="replicate",
                           num_cubes=1, num_pes=P)
        dp_kv = DPPolicy(cube="replicate", pe="row_wise",
                         num_cubes=1, num_pes=P)
        ctx.zeros((1, 8 * D_HEAD), dtype=DTYPE, dp=dp_full, name="q_long_dec")
        k = ctx.zeros((S_kv, D_HEAD),
                      dtype=DTYPE, dp=dp_kv, name="k_long_dec")
        v = ctx.zeros((S_kv, D_HEAD),
                      dtype=DTYPE, dp=dp_kv, name="v_long_dec")
        o = ctx.empty((1, 8 * D_HEAD),
                      dtype=DTYPE, dp=dp_full, name="o_long_dec")
        q = ctx.zeros((1, 8 * D_HEAD),
                      dtype=DTYPE, dp=dp_full, name="q_long_dec_2")
        ctx.launch(
            "gqa_decode_long_32k",
            gqa_attention_decode_long_kernel,
            q, k, v, o,
            1, S_kv, 8, 1, D_HEAD,
            1, P,
            _auto_dim_remap=False,
        )

    result = run_bench(
        topology=topo, bench_fn=_bench_fn,
        device=resolve_device(None), engine_factory=_engine_factory,
    )
    assert result.completion.ok, (
        f"decode at S_kv=32K must complete; got {result.completion}"
    )


# ── Prefill at long context overflows without scope discipline ───────


def test_prefill_long_context_completes_after_scope_discipline():
    """ADR-0063 §A.2 Test Req 3: a sweep at an ``S`` that would overflow
    1 MiB without recycling must complete after scope discipline lands.

    With C=4 and S_kv chosen so per-rank S_local·8·4 > 1 MiB
    (~16K tokens per rank ⇒ S_kv ≥ 64K), the current kernel overflows
    the 1 MiB scratch pool. After Phase 2 (scratch_scope wraps each
    ring step's intermediates; copy_to persists running state), it
    completes.

    This is the headline test that proves the S-ceiling is gone for
    prefill.
    """
    topo = resolve_topology(str(TOPOLOGY_DEFAULT))

    def _bench_fn(ctx):
        configure_sfr_intercube_ring(
            ctx.engine, ctx.spec, _ccl_cfg(), ring_size=4,
        )
        T_q = 4
        S_kv = 65_536  # 64 K — per-rank 16 K, ~2 MB scratch w/o scope
        C = 4
        dp_q = DPPolicy(cube="replicate", pe="replicate",
                        num_cubes=C, num_pes=1)
        dp_kv = DPPolicy(cube="row_wise", pe="replicate",
                         num_cubes=C, num_pes=1)
        dp_o = DPPolicy(cube="row_wise", pe="replicate",
                        num_cubes=C, num_pes=1)
        q = ctx.zeros((T_q, D_HEAD),
                      dtype=DTYPE, dp=dp_q, name="q_long_pre")
        k = ctx.zeros((S_kv, D_HEAD),
                      dtype=DTYPE, dp=dp_kv, name="k_long_pre")
        v = ctx.zeros((S_kv, D_HEAD),
                      dtype=DTYPE, dp=dp_kv, name="v_long_pre")
        o = ctx.empty((T_q * C, D_HEAD),
                      dtype=DTYPE, dp=dp_o, name="o_long_pre")
        ctx.launch(
            "gqa_prefill_long_64k",
            gqa_attention_prefill_long_kernel,
            q, k, v, o,
            T_q, S_kv, D_HEAD, C,
            _auto_dim_remap=False,
        )

    result = run_bench(
        topology=topo, bench_fn=_bench_fn,
        device=resolve_device(None), engine_factory=_engine_factory,
    )
    assert result.completion.ok, (
        f"prefill at S_kv=64K must complete after scope discipline lands; "
        f"got {result.completion}"
    )