Files
kernbench2/tests/test_va_offset.py
T
ywkang 049e3d8bb3 benches: package as kernbench.benches, add @bench registry + list subcommand
Move benches/ -> src/kernbench/benches/ and src/kernbench/cli/probe.py ->
src/kernbench/probes/probe.py. Each bench self-registers via
@bench(name=..., description=...); kernbench list enumerates benches
with auto-assigned indices, --bench accepts kebab-case name or numeric
index. Audit at package-import time fails if any non-underscore module
forgets the decorator. ADR-0010 (EN + KO) updated to reflect the new
resolver path, list subcommand, and probes package separation.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-20 14:42:10 -07:00

227 lines
8.4 KiB
Python

"""VA offset verification: each PE accesses its own local HBM slice.
Verifies that column-wise sharding + VA offset calculation produces DMA
addresses that translate to the correct PE's local HBM — not a remote PE.
Tests:
VO1. Per-PE DMA addresses are correct VAs (2D)
VO2. Each VA translates to the executing PE's own HBM slice (2D)
VO3. End-to-end bench completes (2D, full TP)
VO4. Per-PE DMA addresses are correct VAs (1D)
VO5. Each VA translates to local HBM (1D)
VO6. End-to-end 1D bench completes
"""
from pathlib import Path
import pytest
from kernbench.common.pe_commands import DmaReadCmd, DmaWriteCmd
from kernbench.policy.address.allocator import AddressConfig, PEMemAllocator
from kernbench.policy.address.pe_mmu import PeMMU
from kernbench.policy.address.phyaddr import PhysAddr
from kernbench.policy.address.va_allocator import VirtualAllocator
from kernbench.policy.placement.dp import DPPolicy, resolve_dp_policy
from kernbench.runtime_api.tensor import deploy_tensor
from kernbench.sim_engine.engine import GraphEngine
from kernbench.runtime_api.context import RuntimeContext
from kernbench.runtime_api.types import DeviceSelector
from kernbench.topology.builder import load_topology
from kernbench.triton_emu.tl_context import TLContext, run_kernel
TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
_MB = 1 << 20
_GB = 1 << 30
M, K = 128, 256
DTYPE = "f16"
NUM_PE = 8
ELEM_BYTES = 2
def _copy_kernel_2d(src_ptr, dst_ptr, M, K, tl, DTYPE="f16"):
"""Standard Triton 2D copy. M, K are cube-local."""
pid = tl.program_id(0)
num_pe = tl.num_programs(0)
cols_per_pe = K // num_pe
elem_bytes = 2
offset = pid * M * cols_per_pe * elem_bytes
data = tl.load(src_ptr + offset, shape=(M, cols_per_pe), dtype=DTYPE)
tl.store(dst_ptr + offset, data)
def _copy_kernel_1d(src_ptr, dst_ptr, N, tl, DTYPE="f16"):
"""Standard Triton 1D copy. N is cube-local."""
pid = tl.program_id(0)
num_pe = tl.num_programs(0)
elems_per_pe = N // num_pe
elem_bytes = 2
offset = pid * elems_per_pe * elem_bytes
data = tl.load(src_ptr + offset, shape=(elems_per_pe,), dtype=DTYPE)
tl.store(dst_ptr + offset, data)
def _make_standalone(shape, num_pe=NUM_PE):
"""Create standalone allocators + MMUs for unit testing."""
cfg = AddressConfig(
sip_count=1, cubes_per_sip=1, pes_per_cube=num_pe,
hbm_bytes_per_cube=48 * _GB, hbm_slices_per_cube=num_pe,
tcm_bytes_per_pe=16 * _MB, tcm_scheduler_reserved_bytes=4 * _MB,
sram_bytes_per_cube=32 * _MB,
)
allocators = {
(0, 0, i): PEMemAllocator(sip_id=0, die_id=0, pe_id=i, cfg=cfg)
for i in range(num_pe)
}
va_alloc = VirtualAllocator(va_base=0x1_0000_0000, va_size=64 * _GB, page_size=4096)
mmus = {i: PeMMU(page_size=4096) for i in range(num_pe)}
return cfg, allocators, va_alloc, mmus
# ── VO1. 2D: Per-PE DMA addresses are correct VAs ────────────────────
def test_2d_each_pe_computes_correct_va_offset():
"""2D: each PE generates DMA at va_base + pid * block_bytes."""
src_va = 0x1_0000_0000
dst_va = 0x2_0000_0000
cols_per_pe = K // NUM_PE
block_bytes = M * cols_per_pe * ELEM_BYTES
for pe_id in range(NUM_PE):
tl = TLContext(pe_id=pe_id, num_programs=NUM_PE, dispatch_cycles=0)
run_kernel(_copy_kernel_2d, tl, src_ptr=src_va, dst_ptr=dst_va, M=M, K=K)
reads = [c for c in tl.commands if isinstance(c, DmaReadCmd)]
writes = [c for c in tl.commands if isinstance(c, DmaWriteCmd)]
expected_offset = pe_id * block_bytes
assert reads[0].src_addr == src_va + expected_offset
assert writes[0].dst_addr == dst_va + expected_offset
# ── VO2. 2D: Each VA translates to local HBM ─────────────────────────
def test_2d_va_translates_to_local_hbm():
"""2D: each PE's DMA VA translates to its own HBM slice."""
cfg, allocators, va_alloc, mmus = _make_standalone((M, K))
slice_size = cfg.hbm_slice_bytes
cols_per_pe = K // NUM_PE
block_bytes = M * cols_per_pe * ELEM_BYTES
placement = resolve_dp_policy(
DPPolicy(cube="replicate", pe="column_wise"),
shape=(M, K), itemsize=ELEM_BYTES,
num_pe=NUM_PE, num_cubes=1, target_sip=0,
)
handle = deploy_tensor(
name="src", shape=(M, K), dtype="fp16",
placement=placement, allocators=allocators, va_allocator=va_alloc,
)
# Install per-PE mappings (simulating what context does via MmuMapMsg)
for s in handle.shards:
mmus[s.pe].map(va=handle.va_base + s.offset_bytes, pa=s.pa, size=s.nbytes)
for pe_id in range(NUM_PE):
va = handle.va_base + pe_id * block_bytes
pa = mmus[pe_id].translate(va)
decoded = PhysAddr.decode(pa)
hbm_pe = PhysAddr.hbm_pe_id(decoded.hbm_offset, slice_size)
assert hbm_pe == pe_id, f"PE{pe_id} accessed PE{hbm_pe}'s HBM"
# ── VO3. 2D: End-to-end bench completes ──────────────────────────────
def test_2d_bench_completes():
"""2D: full TP bench with standard Triton kernel pattern."""
graph = load_topology(TOPOLOGY_PATH)
engine = GraphEngine(graph)
ctx = RuntimeContext(
engine=engine, target_device=DeviceSelector("sip:0"),
correlation_id="vo3", spec=graph.spec,
)
from kernbench.benches.va_offset_verify import run as bench_run
bench_run(ctx)
ctx.wait_all()
# ── VO4. 1D: Per-PE DMA addresses ────────────────────────────────────
N_1D = 1024
def test_1d_each_pe_computes_correct_offset():
"""1D: each PE generates DMA at correct offset."""
src_va = 0x1_0000_0000
dst_va = 0x2_0000_0000
elems_per_pe = N_1D // NUM_PE
block_bytes = elems_per_pe * ELEM_BYTES
for pe_id in range(NUM_PE):
tl = TLContext(pe_id=pe_id, num_programs=NUM_PE, dispatch_cycles=0)
run_kernel(_copy_kernel_1d, tl, src_ptr=src_va, dst_ptr=dst_va, N=N_1D)
reads = [c for c in tl.commands if isinstance(c, DmaReadCmd)]
writes = [c for c in tl.commands if isinstance(c, DmaWriteCmd)]
expected_offset = pe_id * block_bytes
assert reads[0].src_addr == src_va + expected_offset
assert writes[0].dst_addr == dst_va + expected_offset
# ── VO5. 1D: VA translates to local HBM ──────────────────────────────
def test_1d_va_translates_to_local_hbm():
"""1D: each PE's DMA VA translates to its own HBM slice."""
cfg, allocators, va_alloc, mmus = _make_standalone((1, N_1D))
slice_size = cfg.hbm_slice_bytes
elems_per_pe = N_1D // NUM_PE
block_bytes = elems_per_pe * ELEM_BYTES
placement = resolve_dp_policy(
DPPolicy(cube="replicate", pe="column_wise"),
shape=(1, N_1D), itemsize=ELEM_BYTES,
num_pe=NUM_PE, num_cubes=1, target_sip=0,
)
handle = deploy_tensor(
name="src_1d", shape=(N_1D,), dtype="fp16",
placement=placement, allocators=allocators, va_allocator=va_alloc,
)
for s in handle.shards:
mmus[s.pe].map(va=handle.va_base + s.offset_bytes, pa=s.pa, size=s.nbytes)
for pe_id in range(NUM_PE):
va = handle.va_base + pe_id * block_bytes
pa = mmus[pe_id].translate(va)
decoded = PhysAddr.decode(pa)
hbm_pe = PhysAddr.hbm_pe_id(decoded.hbm_offset, slice_size)
assert hbm_pe == pe_id, f"1D PE{pe_id} accessed PE{hbm_pe}'s HBM"
# ── VO6. 1D: End-to-end ──────────────────────────────────────────────
def test_1d_e2e_completes():
"""1D: full engine run with column_wise TP sharding."""
graph = load_topology(TOPOLOGY_PATH)
engine = GraphEngine(graph)
ctx = RuntimeContext(
engine=engine, target_device=DeviceSelector("sip:0"),
correlation_id="vo6", spec=graph.spec,
)
# ADR-0026: DPPolicy is intra-device only; SIP scoping comes from the
# RuntimeContext's target_device. This 1D e2e runs on a single SIP.
dp = DPPolicy(cube="column_wise", pe="column_wise")
src = ctx.zeros((N_1D,), dtype=DTYPE, dp=dp, name="src_1d")
dst = ctx.empty((N_1D,), dtype=DTYPE, dp=dp, name="dst_1d")
# launch() auto-localizes N_1D → cube-local N
ctx.launch("va_1d_copy", _copy_kernel_1d, src, dst, N_1D)
ctx.wait_all()