mukesh
e2fe33180d
Adds an optional ``cube_start: int = 0`` field to ``DPPolicy``. In ``resolve_dp_policy`` the generated ``ShardSpec.cube`` is now ``policy.cube_start + cube_id`` instead of just ``cube_id``. With the default value (0) every existing call site resolves to identical ``ShardSpec.cube`` values (cubes 0..num_cubes-1). Why this is needed: the GQA Llama-70B 8-KV-group headline target lays two 2x4 KV-groups per SIP — the first on cubes 0..7 (rows 0..1), the second on cubes 8..15 (rows 2..3). Without ``cube_start``, ``DPPolicy`` can only address the first 8 row-major cubes, so a second launch on the same SIP overlaps the first. ``cube_start=8`` selects the second 2x4 sub-mesh directly. Design choice: scalar ``cube_start`` (vs a 2D ``cube_mesh_origin`` or arbitrary ``cube_ids`` list) was picked because (a) the 2D mesh-mlo kernel already assumes row-major contiguous cubes, (b) it pairs naturally with ``num_cubes`` (range = ``[start, start+count)``), and (c) zero migration churn — every existing call site stays unchanged. Scope: 5 production LOC (one field + one expression in resolve). No kernel changes here; kernels that consume ``program_id(axis=1)`` for ring arithmetic need their own follow-up (see ADR-0022 contract). Tests: 7 new unit tests in ``test_dppolicy_cube_start.py`` covering default behavior preservation (cube_start=0), shifted ranges (cube_start=8 → cubes 8..15), full-SIP CCL pattern, replicate cube policy, shard-count preservation, and uniqueness. ADR-0026 regression suite (12 tests) stays green. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
127 lines
4.5 KiB
Python
127 lines
4.5 KiB
Python
"""Phase 1 spec test for ``DPPolicy.cube_start``.
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``cube_start`` is an optional override that shifts the cube indices in
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``ShardSpec`` generated by ``resolve_dp_policy``. It enables addressing a
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disjoint cube sub-mesh within one SIP (e.g. cubes 8..15 in addition to
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0..7), which the GQA Llama-70B 8-KV-group headline target requires
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(two 2×4 KV-groups per SIP × 4 SIPs = 64 cubes).
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Default ``cube_start=0`` preserves every existing call-site bit-for-bit:
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``DPPolicy(num_cubes=8)`` still resolves to ``ShardSpec.cube ∈ [0, 8)``.
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The CCL milestone bench's full-SIP ``DPPolicy(num_cubes=16)`` likewise
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continues to produce cubes 0..15.
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Phase 1: production code is unchanged → these tests FAIL until the
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Phase 2 diff lands. Phase 2 makes all of them pass.
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"""
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from __future__ import annotations
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from kernbench.policy.placement.dp import DPPolicy, resolve_dp_policy
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# ── Default ``cube_start=0`` preserves existing behavior ─────────────
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def test_dppolicy_default_cube_start_is_zero():
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"""``DPPolicy(num_cubes=8)`` sets ``cube_start=0`` by default."""
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dp = DPPolicy(cube="row_wise", num_cubes=8)
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assert dp.cube_start == 0
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def test_resolve_default_yields_cubes_zero_through_seven():
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"""Backward-compat: default ``cube_start=0`` → cubes 0..num_cubes-1."""
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dp = DPPolicy(cube="row_wise", pe="replicate", num_cubes=8, num_pes=1)
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shards = resolve_dp_policy(
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dp, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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cube_ids = sorted({s.cube for s in shards})
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assert cube_ids == list(range(8))
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def test_resolve_full_sip_default_yields_cubes_zero_through_fifteen():
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"""CCL pattern: ``num_cubes=16, cube_start=0`` → cubes 0..15 unchanged."""
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dp = DPPolicy(cube="row_wise", pe="replicate", num_cubes=16, num_pes=1)
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shards = resolve_dp_policy(
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dp, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=16, target_sip=0,
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)
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cube_ids = sorted({s.cube for s in shards})
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assert cube_ids == list(range(16))
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# ── ``cube_start=N`` shifts cube indices ─────────────────────────────
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def test_resolve_cube_start_eight_yields_cubes_eight_through_fifteen():
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"""``cube_start=8, num_cubes=8`` → ``ShardSpec.cube ∈ [8, 16)``.
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This is the headline-enabling case: the second 2×4 KV-group per SIP
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in the 8-KV-group Llama-70B target lands on cubes 8..15.
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"""
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dp = DPPolicy(
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cube="row_wise", pe="replicate",
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num_cubes=8, num_pes=1, cube_start=8,
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)
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shards = resolve_dp_policy(
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dp, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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cube_ids = sorted({s.cube for s in shards})
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assert cube_ids == list(range(8, 16))
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def test_resolve_cube_start_preserves_shard_count():
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"""Shifting ``cube_start`` does not change the total shard count."""
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dp_default = DPPolicy(
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cube="row_wise", pe="replicate", num_cubes=8, num_pes=1,
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)
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dp_shifted = DPPolicy(
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cube="row_wise", pe="replicate",
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num_cubes=8, num_pes=1, cube_start=8,
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)
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shards_def = resolve_dp_policy(
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dp_default, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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shards_shf = resolve_dp_policy(
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dp_shifted, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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assert len(shards_def) == len(shards_shf)
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# ── ``cube_start`` works with ``cube="replicate"`` too ──────────────
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def test_resolve_cube_start_with_replicate_policy():
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"""``cube="replicate", cube_start=8`` → every cube in [8, 16) gets a copy."""
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dp = DPPolicy(
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cube="replicate", pe="replicate",
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num_cubes=8, num_pes=1, cube_start=8,
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)
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shards = resolve_dp_policy(
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dp, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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cube_ids = sorted({s.cube for s in shards})
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assert cube_ids == list(range(8, 16))
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# ── No duplicates regardless of ``cube_start`` ───────────────────────
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def test_resolve_cube_start_yields_distinct_cube_ids():
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"""For ``pe="replicate", num_pes=1``, every shard has a distinct cube."""
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dp = DPPolicy(
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cube="row_wise", pe="replicate",
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num_cubes=8, num_pes=1, cube_start=8,
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)
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shards = resolve_dp_policy(
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dp, shape=(32, 64), itemsize=2,
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num_pe=1, num_cubes=8, target_sip=0,
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)
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cube_ids = [s.cube for s in shards]
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assert len(cube_ids) == len(set(cube_ids))
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assert all(8 <= c < 16 for c in cube_ids)
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