gqa(decode-4cases): rename bench/kernels/panels with long_ctx token

The 4-cases comparative study is specifically about long-context
decode (LLaMA-3.1-70B, S_kv=128K, T_q=1); the long_ctx token in the
names makes the scope explicit and aligns with the existing
_gqa_attention_decode_long convention.

Renames (mechanical; no semantic change):
  - bench file:   milestone_gqa_decode_4cases.py
                  → milestone_gqa_decode_long_ctx_4cases.py
  - bench name:   milestone-gqa-decode-4cases
                  → milestone-gqa-decode-long-ctx-4cases
  - output dir:   1H_milestone_output/gqa_decode_4cases/
                  → 1H_milestone_output/gqa_decode_long_ctx_4cases/
  - env vars:     GQA_DECODE_4CASES_RUN / _TOPOLOGY
                  → GQA_DECODE_LONG_CTX_4CASES_RUN / _TOPOLOGY
  - 4 kernel files _gqa_attention_decode_<case>.py
                  → _gqa_attention_decode_long_ctx_<case>.py
  - 4 kernel functions gqa_attention_decode_<case>_kernel
                  → gqa_attention_decode_long_ctx_<case>_kernel
  - 4 dispatch kinds  decode_<case> → decode_long_ctx_<case>
  - 4 panel names     single_kv_group_decode_gqa_<case>
                      → single_kv_group_decode_long_ctx_gqa_<case>
  - 4 helper functions _run_decode_panel_<case>
                       → _run_decode_panel_long_ctx_<case>
  - test file renamed in lockstep

Also: Case 4 smoke test now uses its case-specific helper
_run_decode_panel_long_ctx_cube_sp_pe_sp (consistent with Cases 1-3)
instead of the legacy _run_decode_panel from milestone_gqa_headline.
16 tests pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
2026-06-15 16:09:21 -07:00
parent 3c155be8e6
commit ddee28a499
6 changed files with 123 additions and 143 deletions
@@ -31,7 +31,7 @@ from kernbench.benches._gqa_attention_decode_long import _merge_running
TILE_S_KV = 1024 # ADR-0063 §A.2 S_kv-axis tile sweep (per-tile width). TILE_S_KV = 1024 # ADR-0063 §A.2 S_kv-axis tile sweep (per-tile width).
def gqa_attention_decode_cube_repl_pe_sp_kernel( def gqa_attention_decode_long_ctx_cube_repl_pe_sp_kernel(
q_ptr: int, q_ptr: int,
k_ptr: int, k_ptr: int,
v_ptr: int, v_ptr: int,
@@ -31,7 +31,7 @@ from __future__ import annotations
TILE_S_KV = 1024 # match decode_long — per-tile S_kv width (ADR-0063 §A.2). TILE_S_KV = 1024 # match decode_long — per-tile S_kv width (ADR-0063 §A.2).
def gqa_attention_decode_cube_repl_pe_tp_kernel( def gqa_attention_decode_long_ctx_cube_repl_pe_tp_kernel(
q_ptr: int, q_ptr: int,
k_ptr: int, k_ptr: int,
v_ptr: int, v_ptr: int,
@@ -23,7 +23,7 @@ from kernbench.benches._gqa_attention_decode_long import (
) )
def gqa_attention_decode_cube_sp_pe_sp_kernel( def gqa_attention_decode_long_ctx_cube_sp_pe_sp_kernel(
q_ptr: int, q_ptr: int,
k_ptr: int, k_ptr: int,
v_ptr: int, v_ptr: int,
@@ -33,7 +33,7 @@ from kernbench.benches._gqa_attention_decode_long import _merge_running
TILE_S_KV = 1024 # ADR-0063 §A.2 S_kv-axis tile sweep (per-tile width). TILE_S_KV = 1024 # ADR-0063 §A.2 S_kv-axis tile sweep (per-tile width).
def gqa_attention_decode_cube_sp_pe_tp_kernel( def gqa_attention_decode_long_ctx_cube_sp_pe_tp_kernel(
q_ptr: int, q_ptr: int,
k_ptr: int, k_ptr: int,
v_ptr: int, v_ptr: int,
@@ -1,7 +1,8 @@
"""milestone-gqa-decode-4cases: comparative study of 4 decode sharding cases. """milestone-gqa-decode-long-ctx-4cases: long-context decode 4-cases study.
Per GQA_full_deck.pptx slides 11-17: 4 KV-cache sharding strategies on Per GQA_full_deck.pptx slides 11-17: 4 KV-cache sharding strategies on
the LLaMA-3.1-70B single-KV-head group (8 cubes × 8 PEs): the LLaMA-3.1-70B single-KV-head group (8 cubes × 8 PEs) at long
context (S_kv = 128K, T_q = 1):
Case 1 Cube-SP / PE-TP KV split by S_kv across cubes; PEs TP on batch Case 1 Cube-SP / PE-TP KV split by S_kv across cubes; PEs TP on batch
Case 2 Cube-Repl / PE-TP full KV per cube; PEs TP on batch Case 2 Cube-Repl / PE-TP full KV per cube; PEs TP on batch
@@ -13,18 +14,11 @@ invocation and writes per-panel op_log_summary to sweep.json so the
comparative analysis (latency, GEMM/MAC util, comm volume) can be comparative analysis (latency, GEMM/MAC util, comm volume) can be
generated from a single sweep. generated from a single sweep.
Status (initial commit, 5C.D):
- Case 4 panel implemented (uses _gqa_attention_decode_long with
sub_w=4 ADR-0060 §4.2 lrab-adapted center-root reduce; that is
structurally Case 4 per slide 11 with the reduce-to-root variant
of the AR pattern).
- Cases 1-3 panels: TBD in subsequent sub-increments (5C.A/B/C).
Deviation from slide 13: slide prescribes AllReduce (every rank has Deviation from slide 13: slide prescribes AllReduce (every rank has
the answer); the kernel does reduce-to-root (only the lrab center the answer); the kernel does reduce-to-root (only the lrab center
cube has it) per ADR-0060 §4. Treated as the kernbench Case-4 baseline. cube has it) per ADR-0060 §4. Treated as the kernbench Case-4 baseline.
Gated by ``GQA_DECODE_4CASES_RUN=1``. Gated by ``GQA_DECODE_LONG_CTX_4CASES_RUN=1``.
""" """
from __future__ import annotations from __future__ import annotations
@@ -32,17 +26,17 @@ import json
import os import os
from pathlib import Path from pathlib import Path
from kernbench.benches._gqa_attention_decode_cube_repl_pe_sp import ( from kernbench.benches._gqa_attention_decode_long_ctx_cube_repl_pe_sp import (
gqa_attention_decode_cube_repl_pe_sp_kernel, gqa_attention_decode_long_ctx_cube_repl_pe_sp_kernel,
) )
from kernbench.benches._gqa_attention_decode_cube_repl_pe_tp import ( from kernbench.benches._gqa_attention_decode_long_ctx_cube_repl_pe_tp import (
gqa_attention_decode_cube_repl_pe_tp_kernel, gqa_attention_decode_long_ctx_cube_repl_pe_tp_kernel,
) )
from kernbench.benches._gqa_attention_decode_cube_sp_pe_sp import ( from kernbench.benches._gqa_attention_decode_long_ctx_cube_sp_pe_sp import (
gqa_attention_decode_cube_sp_pe_sp_kernel, gqa_attention_decode_long_ctx_cube_sp_pe_sp_kernel,
) )
from kernbench.benches._gqa_attention_decode_cube_sp_pe_tp import ( from kernbench.benches._gqa_attention_decode_long_ctx_cube_sp_pe_tp import (
gqa_attention_decode_cube_sp_pe_tp_kernel, gqa_attention_decode_long_ctx_cube_sp_pe_tp_kernel,
) )
from kernbench.benches.milestone_gqa_headline import ( from kernbench.benches.milestone_gqa_headline import (
_ccl_cfg, _ccl_cfg,
@@ -55,7 +49,7 @@ from kernbench.policy.placement.dp import DPPolicy
_OUTPUT_DIR = ( _OUTPUT_DIR = (
Path(__file__).resolve().parent Path(__file__).resolve().parent
/ "1H_milestone_output" / "1H_milestone_output"
/ "gqa_decode_4cases" / "gqa_decode_long_ctx_4cases"
) )
_SWEEP_JSON = _OUTPUT_DIR / "sweep.json" _SWEEP_JSON = _OUTPUT_DIR / "sweep.json"
@@ -64,10 +58,10 @@ _SWEEP_JSON = _OUTPUT_DIR / "sweep.json"
_PANELS = ( _PANELS = (
"single_kv_group_decode_gqa_cube_sp_pe_sp", # Case 4 ★ optimal "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_sp", # Case 4 ★ optimal
"single_kv_group_decode_gqa_cube_repl_pe_tp", # Case 2 (no comm; 8× memory) "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_tp", # Case 2 (no comm; 8× memory)
"single_kv_group_decode_gqa_cube_repl_pe_sp", # Case 3 (intra-CUBE AR only; 8× memory) "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_sp", # Case 3 (intra-CUBE AR only; 8× memory)
"single_kv_group_decode_gqa_cube_sp_pe_tp", # Case 1 (inter-CUBE lrab only; PE-TP B=1 waste) "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_tp", # Case 1 (inter-CUBE lrab only; PE-TP B=1 waste)
) )
# Each entry: (kind, panel-specific params). # Each entry: (kind, panel-specific params).
@@ -76,7 +70,7 @@ _PANELS = (
# 8 cubes (head-parallel group), 8 PEs/cube # 8 cubes (head-parallel group), 8 PEs/cube
# S_kv = 128K (long-context decode), T_q = 1 (one new token per pass) # S_kv = 128K (long-context decode), T_q = 1 (one new token per pass)
_PANEL_DISPATCH: dict[str, tuple[str, dict]] = { _PANEL_DISPATCH: dict[str, tuple[str, dict]] = {
"single_kv_group_decode_gqa_cube_sp_pe_sp": ("decode_cube_sp_pe_sp", { "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_sp": ("decode_long_ctx_cube_sp_pe_sp", {
# Case 4: KV split 64-way (Cube-SP × PE-SP), 2-level reduce. # Case 4: KV split 64-way (Cube-SP × PE-SP), 2-level reduce.
# The sub_w=4/sub_h=2 lrab center-root geometry (root cube 6) is # The sub_w=4/sub_h=2 lrab center-root geometry (root cube 6) is
# baked into the Case-4 wrapper kernel. # baked into the Case-4 wrapper kernel.
@@ -84,7 +78,7 @@ _PANEL_DISPATCH: dict[str, tuple[str, dict]] = {
"T_q": 1, "S_kv": 131_072, "T_q": 1, "S_kv": 131_072,
"d_head": 128, "h_q": 8, "h_kv": 1, "d_head": 128, "h_q": 8, "h_kv": 1,
}), }),
"single_kv_group_decode_gqa_cube_repl_pe_tp": ("decode_cube_repl_pe_tp", { "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_tp": ("decode_long_ctx_cube_repl_pe_tp", {
# Case 2: K, V replicated everywhere (8× memory waste); PEs TP # Case 2: K, V replicated everywhere (8× memory waste); PEs TP
# on batch. For B=1 only one rank works (slide-11 PE-TP waste). # on batch. For B=1 only one rank works (slide-11 PE-TP waste).
# No inter-rank communication. # No inter-rank communication.
@@ -92,7 +86,7 @@ _PANEL_DISPATCH: dict[str, tuple[str, dict]] = {
"T_q": 1, "S_kv": 131_072, "T_q": 1, "S_kv": 131_072,
"d_head": 128, "h_q": 8, "h_kv": 1, "d_head": 128, "h_q": 8, "h_kv": 1,
}), }),
"single_kv_group_decode_gqa_cube_repl_pe_sp": ("decode_cube_repl_pe_sp", { "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_sp": ("decode_long_ctx_cube_repl_pe_sp", {
# Case 3: K, V replicated per cube (8× memory); PEs SP on S_kv # Case 3: K, V replicated per cube (8× memory); PEs SP on S_kv
# within each cube. Intra-CUBE 8-way reduce; no inter-CUBE comm # within each cube. Intra-CUBE 8-way reduce; no inter-CUBE comm
# (every cube ends with full answer; designated writer = cube 0). # (every cube ends with full answer; designated writer = cube 0).
@@ -100,7 +94,7 @@ _PANEL_DISPATCH: dict[str, tuple[str, dict]] = {
"T_q": 1, "S_kv": 131_072, "T_q": 1, "S_kv": 131_072,
"d_head": 128, "h_q": 8, "h_kv": 1, "d_head": 128, "h_q": 8, "h_kv": 1,
}), }),
"single_kv_group_decode_gqa_cube_sp_pe_tp": ("decode_cube_sp_pe_tp", { "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_tp": ("decode_long_ctx_cube_sp_pe_tp", {
# Case 1: K, V split across cubes (S_local = S_kv/C per cube); # Case 1: K, V split across cubes (S_local = S_kv/C per cube);
# PEs TP on batch — at B=1 only PE 0 of each cube works (PE-TP # PEs TP on batch — at B=1 only PE 0 of each cube works (PE-TP
# waste). Inter-CUBE lrab AR (root = cube 6); no intra-CUBE comm. # waste). Inter-CUBE lrab AR (root = cube 6); no intra-CUBE comm.
@@ -114,7 +108,7 @@ _PANEL_DISPATCH: dict[str, tuple[str, dict]] = {
# ── Per-panel runner ───────────────────────────────────────────────── # ── Per-panel runner ─────────────────────────────────────────────────
def _run_decode_panel_cube_repl_pe_tp( def _run_decode_panel_long_ctx_cube_repl_pe_tp(
ctx, *, panel: str, C: int, P: int, ctx, *, panel: str, C: int, P: int,
T_q: int, S_kv: int, T_q: int, S_kv: int,
d_head: int, h_q: int, h_kv: int, d_head: int, h_q: int, h_kv: int,
@@ -138,14 +132,14 @@ def _run_decode_panel_cube_repl_pe_tp(
o = ctx.empty((T_q, h_q * d_head), o = ctx.empty((T_q, h_q * d_head),
dtype="f16", dp=dp_repl, name=f"{panel}_o") dtype="f16", dp=dp_repl, name=f"{panel}_o")
ctx.launch( ctx.launch(
panel, gqa_attention_decode_cube_repl_pe_tp_kernel, panel, gqa_attention_decode_long_ctx_cube_repl_pe_tp_kernel,
q, k, v, o, q, k, v, o,
T_q, S_kv, h_q, h_kv, d_head, C, P, T_q, S_kv, h_q, h_kv, d_head, C, P,
_auto_dim_remap=False, _auto_dim_remap=False,
) )
def _run_decode_panel_cube_repl_pe_sp( def _run_decode_panel_long_ctx_cube_repl_pe_sp(
ctx, *, panel: str, C: int, P: int, ctx, *, panel: str, C: int, P: int,
T_q: int, S_kv: int, T_q: int, S_kv: int,
d_head: int, h_q: int, h_kv: int, d_head: int, h_q: int, h_kv: int,
@@ -171,14 +165,14 @@ def _run_decode_panel_cube_repl_pe_sp(
o = ctx.empty((T_q, h_q * d_head), o = ctx.empty((T_q, h_q * d_head),
dtype="f16", dp=dp_full, name=f"{panel}_o") dtype="f16", dp=dp_full, name=f"{panel}_o")
ctx.launch( ctx.launch(
panel, gqa_attention_decode_cube_repl_pe_sp_kernel, panel, gqa_attention_decode_long_ctx_cube_repl_pe_sp_kernel,
q, k, v, o, q, k, v, o,
T_q, S_kv, h_q, h_kv, d_head, C, P, T_q, S_kv, h_q, h_kv, d_head, C, P,
_auto_dim_remap=False, _auto_dim_remap=False,
) )
def _run_decode_panel_cube_sp_pe_tp( def _run_decode_panel_long_ctx_cube_sp_pe_tp(
ctx, *, panel: str, C: int, P: int, ctx, *, panel: str, C: int, P: int,
T_q: int, S_kv: int, T_q: int, S_kv: int,
d_head: int, h_q: int, h_kv: int, d_head: int, h_q: int, h_kv: int,
@@ -205,14 +199,14 @@ def _run_decode_panel_cube_sp_pe_tp(
o = ctx.empty((T_q, h_q * d_head), o = ctx.empty((T_q, h_q * d_head),
dtype="f16", dp=dp_full, name=f"{panel}_o") dtype="f16", dp=dp_full, name=f"{panel}_o")
ctx.launch( ctx.launch(
panel, gqa_attention_decode_cube_sp_pe_tp_kernel, panel, gqa_attention_decode_long_ctx_cube_sp_pe_tp_kernel,
q, k, v, o, q, k, v, o,
T_q, S_kv, h_q, h_kv, d_head, C, P, T_q, S_kv, h_q, h_kv, d_head, C, P,
_auto_dim_remap=False, _auto_dim_remap=False,
) )
def _run_decode_panel_cube_sp_pe_sp( def _run_decode_panel_long_ctx_cube_sp_pe_sp(
ctx, *, panel: str, C: int, P: int, ctx, *, panel: str, C: int, P: int,
T_q: int, S_kv: int, T_q: int, S_kv: int,
d_head: int, h_q: int, h_kv: int, d_head: int, h_q: int, h_kv: int,
@@ -237,7 +231,7 @@ def _run_decode_panel_cube_sp_pe_sp(
o = ctx.empty((T_q, h_q * d_head), o = ctx.empty((T_q, h_q * d_head),
dtype="f16", dp=dp_full, name=f"{panel}_o") dtype="f16", dp=dp_full, name=f"{panel}_o")
ctx.launch( ctx.launch(
panel, gqa_attention_decode_cube_sp_pe_sp_kernel, panel, gqa_attention_decode_long_ctx_cube_sp_pe_sp_kernel,
q, k, v, o, q, k, v, o,
T_q, S_kv, h_q, h_kv, d_head, C, P, T_q, S_kv, h_q, h_kv, d_head, C, P,
_auto_dim_remap=False, _auto_dim_remap=False,
@@ -248,17 +242,17 @@ def _make_bench_fn(panel: str):
kind, params = _PANEL_DISPATCH[panel] kind, params = _PANEL_DISPATCH[panel]
def _bench_fn(ctx): def _bench_fn(ctx):
if kind == "decode_cube_sp_pe_sp": if kind == "decode_long_ctx_cube_sp_pe_sp":
_run_decode_panel_cube_sp_pe_sp(ctx, panel=panel, **params) _run_decode_panel_long_ctx_cube_sp_pe_sp(ctx, panel=panel, **params)
elif kind == "decode_cube_repl_pe_tp": elif kind == "decode_long_ctx_cube_repl_pe_tp":
_run_decode_panel_cube_repl_pe_tp(ctx, panel=panel, **params) _run_decode_panel_long_ctx_cube_repl_pe_tp(ctx, panel=panel, **params)
elif kind == "decode_cube_repl_pe_sp": elif kind == "decode_long_ctx_cube_repl_pe_sp":
_run_decode_panel_cube_repl_pe_sp(ctx, panel=panel, **params) _run_decode_panel_long_ctx_cube_repl_pe_sp(ctx, panel=panel, **params)
elif kind == "decode_cube_sp_pe_tp": elif kind == "decode_long_ctx_cube_sp_pe_tp":
_run_decode_panel_cube_sp_pe_tp(ctx, panel=panel, **params) _run_decode_panel_long_ctx_cube_sp_pe_tp(ctx, panel=panel, **params)
else: else:
raise RuntimeError( raise RuntimeError(
f"milestone-gqa-decode-4cases panel {panel!r} has " f"milestone-gqa-decode-long-ctx-4cases panel {panel!r} has "
f"unsupported kind={kind!r}." f"unsupported kind={kind!r}."
) )
return _bench_fn return _bench_fn
@@ -280,7 +274,7 @@ def _run_panel(panel: str, topology: str) -> dict:
) )
if not result.completion.ok: if not result.completion.ok:
raise RuntimeError( raise RuntimeError(
f"milestone-gqa-decode-4cases panel {panel!r} failed: " f"milestone-gqa-decode-long-ctx-4cases panel {panel!r} failed: "
f"{result.completion}" f"{result.completion}"
) )
kind, params = _PANEL_DISPATCH[panel] kind, params = _PANEL_DISPATCH[panel]
@@ -296,25 +290,26 @@ def _run_panel(panel: str, topology: str) -> dict:
@bench( @bench(
name="milestone-gqa-decode-4cases", name="milestone-gqa-decode-long-ctx-4cases",
description=( description=(
"Comparative decode study of 4 KV-cache sharding cases on the " "Long-context decode 4-cases comparative study on the "
"LLaMA-3.1-70B single-KV-head group (8 cubes × 8 PEs)." "LLaMA-3.1-70B single-KV-head group (8 cubes × 8 PEs)."
), ),
) )
def run(torch) -> None: def run(torch) -> None:
"""Drive the registered decode case panels; write sweep.json. """Drive the registered decode case panels; write sweep.json.
Gated by GQA_DECODE_4CASES_RUN=1. Gated by GQA_DECODE_LONG_CTX_4CASES_RUN=1.
""" """
_OUTPUT_DIR.mkdir(parents=True, exist_ok=True) _OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
if not os.environ.get("GQA_DECODE_4CASES_RUN"): if not os.environ.get("GQA_DECODE_LONG_CTX_4CASES_RUN"):
raise RuntimeError( raise RuntimeError(
"milestone-gqa-decode-4cases needs GQA_DECODE_4CASES_RUN=1." "milestone-gqa-decode-long-ctx-4cases needs "
"GQA_DECODE_LONG_CTX_4CASES_RUN=1."
) )
topology = os.environ.get( topology = os.environ.get(
"GQA_DECODE_4CASES_TOPOLOGY", "topology.yaml", "GQA_DECODE_LONG_CTX_4CASES_TOPOLOGY", "topology.yaml",
) )
rows = [_run_panel(panel, topology) for panel in _PANELS] rows = [_run_panel(panel, topology) for panel in _PANELS]
sweep = { sweep = {
@@ -324,5 +319,5 @@ def run(torch) -> None:
} }
_SWEEP_JSON.write_text(json.dumps(sweep, indent=2)) _SWEEP_JSON.write_text(json.dumps(sweep, indent=2))
print( print(
f" milestone-gqa-decode-4cases: {len(rows)} rows -> {_SWEEP_JSON}" f" milestone-gqa-decode-long-ctx-4cases: {len(rows)} rows -> {_SWEEP_JSON}"
) )
@@ -1,4 +1,4 @@
"""Tests for the decode 4-cases comparative-study bench. """Tests for the long-context decode 4-cases comparative-study bench.
Per ``GQA_full_deck.pptx`` slides 11-17, the 4 cases differ in how KV Per ``GQA_full_deck.pptx`` slides 11-17, the 4 cases differ in how KV
cache is sharded across the 8 cubes and 8 PEs of a single KV-head cache is sharded across the 8 cubes and 8 PEs of a single KV-head
@@ -9,28 +9,15 @@ group on LLaMA-3.1-70B GQA:
Case 3 Cube-Repl / PE-SP full KV per cube; PEs SP on S_kv (intra-cube AR) Case 3 Cube-Repl / PE-SP full KV per cube; PEs SP on S_kv (intra-cube AR)
Case 4 Cube-SP / PE-SP KV split 64-way; 2-phase AR on (m,,O) optimal Case 4 Cube-SP / PE-SP KV split 64-way; 2-phase AR on (m,,O) optimal
This file grows as each case lands. Phase 1 of 5C.D adds Case 4 first,
which is structurally the existing ``_gqa_attention_decode_long.py`` at
``sub_w=4`` (Increment 2's lrab-adapted center-root reduce). The Phase 2
production change introduces a new bench file
``src/kernbench/benches/milestone_gqa_decode_4cases.py`` housing the 4
case panels under a single ``milestone-gqa-decode-4cases`` entry, and
extends ``_run_decode_panel`` in ``milestone_gqa_headline`` to accept
``sub_w``/``d_head``/``h_q``/``h_kv`` overrides.
Deviation from slide 13: slide prescribes AllReduce on (m,,O); the Deviation from slide 13: slide prescribes AllReduce on (m,,O); the
kernel does reduce-to-root (only the lrab center cube has the answer) kernel does reduce-to-root (only the lrab center cube has the answer)
per ADR-0060 §4. Treated as the kernbench Case-4 baseline. per ADR-0060 §4. Treated as the kernbench Case-4 baseline.
Phase 1: tests only. T1, T2, T3, T4 fail today (new bench file does
not yet exist; ``_run_decode_panel`` does not yet accept ``sub_w``).
""" """
from __future__ import annotations from __future__ import annotations
import re import re
from pathlib import Path from pathlib import Path
from kernbench.benches.milestone_gqa_headline import _run_decode_panel
from kernbench.runtime_api.bench_runner import run_bench from kernbench.runtime_api.bench_runner import run_bench
from kernbench.runtime_api.types import resolve_device from kernbench.runtime_api.types import resolve_device
from kernbench.sim_engine.engine import GraphEngine from kernbench.sim_engine.engine import GraphEngine
@@ -38,10 +25,10 @@ from kernbench.topology.builder import resolve_topology
TOPOLOGY_DEFAULT = Path(__file__).resolve().parents[2] / "topology.yaml" TOPOLOGY_DEFAULT = Path(__file__).resolve().parents[2] / "topology.yaml"
_CASE4_PANEL = "single_kv_group_decode_gqa_cube_sp_pe_sp" _CASE4_PANEL = "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_sp"
_CASE3_PANEL = "single_kv_group_decode_gqa_cube_repl_pe_sp" _CASE3_PANEL = "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_sp"
_CASE2_PANEL = "single_kv_group_decode_gqa_cube_repl_pe_tp" _CASE2_PANEL = "single_kv_group_decode_long_ctx_gqa_cube_repl_pe_tp"
_CASE1_PANEL = "single_kv_group_decode_gqa_cube_sp_pe_tp" _CASE1_PANEL = "single_kv_group_decode_long_ctx_gqa_cube_sp_pe_tp"
_CUBE_RE = re.compile(r"\bcube(\d+)\b") _CUBE_RE = re.compile(r"\bcube(\d+)\b")
@@ -64,20 +51,26 @@ def _dma_write_cubes(op_log) -> list[int]:
return cubes return cubes
# ── Case 4 (Cube-SP × PE-SP) — ★ optimal ────────────────────────────
def _run_case4_smoke(*, S_kv: int): def _run_case4_smoke(*, S_kv: int):
"""Drive the Case 4 decode panel via ``_run_decode_panel``. """Drive the Case 4 decode panel via the case-specific runner.
Uses ``S_kv=8192`` (smoke) to keep test time bounded; the headline Uses ``S_kv=8192`` (smoke) to keep test time bounded; the headline
``S_kv=128K`` runs come from ``kernbench run --bench ``S_kv=128K`` runs come from ``kernbench run --bench
milestone-gqa-decode-4cases``, not pytest. milestone-gqa-decode-long-ctx-4cases``, not pytest.
""" """
from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_run_decode_panel_long_ctx_cube_sp_pe_sp,
)
topo = resolve_topology(str(TOPOLOGY_DEFAULT)) topo = resolve_topology(str(TOPOLOGY_DEFAULT))
def _bench_fn(ctx): def _bench_fn(ctx):
_run_decode_panel( _run_decode_panel_long_ctx_cube_sp_pe_sp(
ctx, panel=_CASE4_PANEL, ctx, panel=_CASE4_PANEL,
C=8, P=8, sub_w=4, C=8, P=8,
S_kv=S_kv, T_q=1, S_kv=S_kv,
d_head=128, h_q=8, h_kv=1, d_head=128, h_q=8, h_kv=1,
) )
@@ -88,11 +81,11 @@ def _run_case4_smoke(*, S_kv: int):
) )
# ── T1: Case 4 panel is registered in the new bench ────────────────── # ── Case 4 — T1: panel is registered in the bench ──────────────────
def test_case4_panel_registered(): def test_case4_panel_registered():
"""The Case 4 panel must be in the new bench's ``_PANELS`` + """The Case 4 panel must be in the bench's ``_PANELS`` +
``_PANEL_DISPATCH`` with the expected LLaMA-3.1-70B target dims. ``_PANEL_DISPATCH`` with the expected LLaMA-3.1-70B target dims.
Headline config: Headline config:
@@ -103,10 +96,9 @@ def test_case4_panel_registered():
d_head = 128, h_q = 8, h_kv = 1 d_head = 128, h_q = 8, h_kv = 1
The lrab sub_w=4 / sub_h=2 geometry is baked into the Case 4 The lrab sub_w=4 / sub_h=2 geometry is baked into the Case 4
wrapper kernel (``_gqa_attention_decode_cube_sp_pe_sp.py``); it wrapper kernel; it is not a panel parameter.
is not a panel parameter.
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_PANEL_DISPATCH, _PANEL_DISPATCH,
_PANELS, _PANELS,
) )
@@ -115,8 +107,8 @@ def test_case4_panel_registered():
) )
assert _CASE4_PANEL in _PANEL_DISPATCH assert _CASE4_PANEL in _PANEL_DISPATCH
kind, params = _PANEL_DISPATCH[_CASE4_PANEL] kind, params = _PANEL_DISPATCH[_CASE4_PANEL]
assert kind == "decode_cube_sp_pe_sp", ( assert kind == "decode_long_ctx_cube_sp_pe_sp", (
f"kind={kind!r}, expected 'decode_cube_sp_pe_sp'" f"kind={kind!r}, expected 'decode_long_ctx_cube_sp_pe_sp'"
) )
assert params.get("C") == 8 assert params.get("C") == 8
assert params.get("P") == 8 assert params.get("P") == 8
@@ -127,26 +119,19 @@ def test_case4_panel_registered():
assert params.get("h_kv") == 1 assert params.get("h_kv") == 1
# ── T2: Case 4 runner drives the kernel to completion ─────────────── # ── Case 4 — T2: runner drives the kernel to completion ─────────────
def test_case4_runner_smoke(): def test_case4_runner_smoke():
"""``_run_decode_panel`` must accept the new ``sub_w``, """Case 4 runner drives the new kernel to completion at smoke S_kv."""
``d_head``, ``h_q``, ``h_kv`` kwargs and launch the kernel at
``(C, P, sub_w) = (8, 8, 4)`` (the Case 4 / lrab path).
Smoke uses ``S_kv=8192`` so the simulation completes quickly. The
headline 128K dims run via ``kernbench run --bench
milestone-gqa-decode-4cases``.
"""
result = _run_case4_smoke(S_kv=8192) result = _run_case4_smoke(S_kv=8192)
assert result.completion.ok, ( assert result.completion.ok, (
f"Case 4 decode smoke at C=8 P=8 sub_w=4 must complete; " f"Case 4 decode smoke at C=8 P=8 must complete; "
f"got {result.completion}" f"got {result.completion}"
) )
# ── T3: reduce-to-root lands at the lrab center cube (cube 6) ─────── # ── Case 4 — T3: reduce-to-root at the lrab center cube (cube 6) ────
def test_case4_root_at_center_cube_6(): def test_case4_root_at_center_cube_6():
@@ -165,7 +150,37 @@ def test_case4_root_at_center_cube_6():
) )
# ── T4: 2-phase AR ipcq pattern matches the predicted Case-4 traffic ─ # ── Case 4 — T4: 2-phase AR ipcq pattern matches Case-4 traffic ────
def test_case4_two_level_ar_ipcq_pattern():
"""Total ipcq_copy for the Case 4 reduce at (C, P, sub_w) =
(8, 8, 4):
Intra-CUBE (per CUBE = 8 PEs in a 2×4 grid):
row chain along intra_W: cols 1,2,3 each row × 2 rows ×
3 tensors = 18
col bridge along intra_N: pe4 only × 3 tensors = 3
per-CUBE intra total = 21
× 8 CUBEs = 168
Inter-CUBE lrab (sub_w=4, sub_h=2):
Phase 1 row reduce 3 sends/row × 3 tensors × 2 rows = 18
Phase 2 col reduce cube 2 S × 3 tensors = 3
inter-CUBE total = 21
Grand total: 168 + 21 = 189
"""
result = _run_case4_smoke(S_kv=8192)
assert result.completion.ok
n_copy = _count(result.engine.op_log, "ipcq_copy")
assert n_copy == 189, (
f"Case 4 expected 189 ipcq_copy "
f"(168 intra-CUBE + 21 inter-CUBE lrab); got {n_copy}"
)
# ── Case 2 (Cube-Repl × PE-TP) ──────────────────────────────────────
def _run_case2_smoke(*, S_kv: int): def _run_case2_smoke(*, S_kv: int):
@@ -175,13 +190,13 @@ def _run_case2_smoke(*, S_kv: int):
slide-11 memory waste); for B=1 only one rank does the work; no slide-11 memory waste); for B=1 only one rank does the work; no
inter-rank comm. inter-rank comm.
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_run_decode_panel_cube_repl_pe_tp, _run_decode_panel_long_ctx_cube_repl_pe_tp,
) )
topo = resolve_topology(str(TOPOLOGY_DEFAULT)) topo = resolve_topology(str(TOPOLOGY_DEFAULT))
def _bench_fn(ctx): def _bench_fn(ctx):
_run_decode_panel_cube_repl_pe_tp( _run_decode_panel_long_ctx_cube_repl_pe_tp(
ctx, panel=_CASE2_PANEL, ctx, panel=_CASE2_PANEL,
C=8, P=8, C=8, P=8,
T_q=1, S_kv=S_kv, T_q=1, S_kv=S_kv,
@@ -207,7 +222,7 @@ def test_case2_panel_registered():
For B=1 only one rank works (PEs 1-7 idle slide-11 calls For B=1 only one rank works (PEs 1-7 idle slide-11 calls
out this PE-TP waste). out this PE-TP waste).
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_PANEL_DISPATCH, _PANEL_DISPATCH,
_PANELS, _PANELS,
) )
@@ -216,7 +231,7 @@ def test_case2_panel_registered():
) )
assert _CASE2_PANEL in _PANEL_DISPATCH assert _CASE2_PANEL in _PANEL_DISPATCH
kind, params = _PANEL_DISPATCH[_CASE2_PANEL] kind, params = _PANEL_DISPATCH[_CASE2_PANEL]
assert kind == "decode_cube_repl_pe_tp" assert kind == "decode_long_ctx_cube_repl_pe_tp"
assert params.get("C") == 8 assert params.get("C") == 8
assert params.get("P") == 8 assert params.get("P") == 8
assert params.get("T_q") == 1 assert params.get("T_q") == 1
@@ -281,13 +296,13 @@ def _run_case3_smoke(*, S_kv: int):
8-way across PEs within each cube. Intra-CUBE 8-way reduce on 8-way across PEs within each cube. Intra-CUBE 8-way reduce on
(m, , O); no inter-CUBE comm (every cube ends with full answer). (m, , O); no inter-CUBE comm (every cube ends with full answer).
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_run_decode_panel_cube_repl_pe_sp, _run_decode_panel_long_ctx_cube_repl_pe_sp,
) )
topo = resolve_topology(str(TOPOLOGY_DEFAULT)) topo = resolve_topology(str(TOPOLOGY_DEFAULT))
def _bench_fn(ctx): def _bench_fn(ctx):
_run_decode_panel_cube_repl_pe_sp( _run_decode_panel_long_ctx_cube_repl_pe_sp(
ctx, panel=_CASE3_PANEL, ctx, panel=_CASE3_PANEL,
C=8, P=8, C=8, P=8,
T_q=1, S_kv=S_kv, T_q=1, S_kv=S_kv,
@@ -311,7 +326,7 @@ def test_case3_panel_registered():
Case 3: Cube-Repl × PE-SP. K, V replicated per cube; PEs SP on Case 3: Cube-Repl × PE-SP. K, V replicated per cube; PEs SP on
S_kv. Intra-CUBE 8-way AR; no inter-CUBE comm. S_kv. Intra-CUBE 8-way AR; no inter-CUBE comm.
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_PANEL_DISPATCH, _PANEL_DISPATCH,
_PANELS, _PANELS,
) )
@@ -320,7 +335,7 @@ def test_case3_panel_registered():
) )
assert _CASE3_PANEL in _PANEL_DISPATCH assert _CASE3_PANEL in _PANEL_DISPATCH
kind, params = _PANEL_DISPATCH[_CASE3_PANEL] kind, params = _PANEL_DISPATCH[_CASE3_PANEL]
assert kind == "decode_cube_repl_pe_sp" assert kind == "decode_long_ctx_cube_repl_pe_sp"
assert params.get("C") == 8 assert params.get("C") == 8
assert params.get("P") == 8 assert params.get("P") == 8
assert params.get("T_q") == 1 assert params.get("T_q") == 1
@@ -401,13 +416,13 @@ def _run_case1_smoke(*, S_kv: int):
each cube has work; PEs 1-7 idle. Inter-CUBE 8-way reduce via the each cube has work; PEs 1-7 idle. Inter-CUBE 8-way reduce via the
lrab-adapted center-root pattern (root cube 6); no intra-CUBE comm. lrab-adapted center-root pattern (root cube 6); no intra-CUBE comm.
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_run_decode_panel_cube_sp_pe_tp, _run_decode_panel_long_ctx_cube_sp_pe_tp,
) )
topo = resolve_topology(str(TOPOLOGY_DEFAULT)) topo = resolve_topology(str(TOPOLOGY_DEFAULT))
def _bench_fn(ctx): def _bench_fn(ctx):
_run_decode_panel_cube_sp_pe_tp( _run_decode_panel_long_ctx_cube_sp_pe_tp(
ctx, panel=_CASE1_PANEL, ctx, panel=_CASE1_PANEL,
C=8, P=8, C=8, P=8,
T_q=1, S_kv=S_kv, T_q=1, S_kv=S_kv,
@@ -432,7 +447,7 @@ def test_case1_panel_registered():
batch. At B=1 only PE 0 of each cube works (PE-TP waste). batch. At B=1 only PE 0 of each cube works (PE-TP waste).
Inter-CUBE lrab AR; no intra-CUBE comm. Inter-CUBE lrab AR; no intra-CUBE comm.
""" """
from kernbench.benches.milestone_gqa_decode_4cases import ( from kernbench.benches.milestone_gqa_decode_long_ctx_4cases import (
_PANEL_DISPATCH, _PANEL_DISPATCH,
_PANELS, _PANELS,
) )
@@ -441,7 +456,7 @@ def test_case1_panel_registered():
) )
assert _CASE1_PANEL in _PANEL_DISPATCH assert _CASE1_PANEL in _PANEL_DISPATCH
kind, params = _PANEL_DISPATCH[_CASE1_PANEL] kind, params = _PANEL_DISPATCH[_CASE1_PANEL]
assert kind == "decode_cube_sp_pe_tp" assert kind == "decode_long_ctx_cube_sp_pe_tp"
assert params.get("C") == 8 assert params.get("C") == 8
assert params.get("P") == 8 assert params.get("P") == 8
assert params.get("T_q") == 1 assert params.get("T_q") == 1
@@ -507,33 +522,3 @@ def test_case1_root_at_center_cube_6():
f"Case 1 root must be the lrab center cube 6; " f"Case 1 root must be the lrab center cube 6; "
f"got cubes={sorted(distinct)}" f"got cubes={sorted(distinct)}"
) )
# ── Case 4 — T4 (existing, kept) ────────────────────────────────────
def test_case4_two_level_ar_ipcq_pattern():
"""Total ipcq_copy for the Case 4 reduce at (C, P, sub_w) =
(8, 8, 4):
Intra-CUBE (per CUBE = 8 PEs in a 2×4 grid):
row chain along intra_W: cols 1,2,3 each row × 2 rows ×
3 tensors = 18
col bridge along intra_N: pe4 only × 3 tensors = 3
per-CUBE intra total = 21
× 8 CUBEs = 168
Inter-CUBE lrab (sub_w=4, sub_h=2):
Phase 1 row reduce 3 sends/row × 3 tensors × 2 rows = 18
Phase 2 col reduce cube 2 S × 3 tensors = 3
inter-CUBE total = 21
Grand total: 168 + 21 = 189
"""
result = _run_case4_smoke(S_kv=8192)
assert result.completion.ok
n_copy = _count(result.engine.op_log, "ipcq_copy")
assert n_copy == 189, (
f"Case 4 expected 189 ipcq_copy "
f"(168 intra-CUBE + 21 inter-CUBE lrab); got {n_copy}"
)