Latency model: HBM PC striping + chunk-loop drain (ADR-0033)

Previous model double-counted slow-upstream paths (e.g., 64KB via UCIe
128 GB/s was ~2x pessimistic). HBM CTRL now distributes bursts across
8 pseudo-channels via global round-robin, with per-chunk commit timing
that pipelines correctly against the bottleneck link's data arrival.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-14 21:59:07 -07:00
parent f6d262e359
commit 5fdb6f8797
11 changed files with 1192 additions and 52 deletions
@@ -33,12 +33,17 @@ Each PE has a notion of “local HBM” that must guarantee full HBM bandwidth,
- This guarantee is modeled by:
- a dedicated logical path and/or service model that enforces HBM BW at the PE-local-HBM interaction point,
- while still incurring non-zero latency along explicitly modeled components.
- HBM CTRL internal modeling (PC striping, cut-through, scheduling fidelity)
is consolidated in ADR-0033 (Latency Model: Assumptions and Known
Simplifications). The aggregate BW guarantee here remains the contract;
ADR-0033 documents how the per-PC model realizes it and which scheduler
effects are intentionally simplified.
### D3. Remote PE HBM semantics (intra-cube)
- A PE that accesses another PE's local HBM traverses the router mesh:
- PE_DMA → local router → (mesh hops) → target PE's router → HBM_CTRL
- Router mesh bandwidth and hop count may limit remote HBM access relative to local access.
- A PE that accesses another PE's local HBM traverses the NOC:
- PE_DMA → NOC → (fabric hops) → target PE's NOC port → HBM_CTRL
- NOC bandwidth and hop count may limit remote HBM access relative to local access.
### D4. Non-local HBM semantics (inter-cube / inter-SIP)
@@ -0,0 +1,99 @@
# ADR-0033 — Latency Model: Assumptions and Known Simplifications
## Status
Accepted
## Context
The simulator is an analytical, event-driven performance model — not a
cycle-accurate or RTL-level simulator. Many real-HW effects are approximated
or omitted by design. To keep the model auditable and reviewable as a whole,
this ADR consolidates the assumptions in one place. Individual component ADRs
(ADR-0015, ADR-0019, ADR-0004) define the *mechanisms*; this document defines
the *limits of fidelity*.
## Decisions
### D1. Modeled precisely
- **Per-directed-edge BW occupancy** (FIFO serialization via `available_at`) —
ADR-0015 D2.
- **Per-component switching/overhead latency** (`overhead_ns` attr).
- **HBM per-pseudo-channel parallelism** via stateless `pc_avail[N]` array
with global round-robin chunking. Burst granularity tunable
(`burst_bytes`, default 256B). Read and write share each PC's
`available_at` (real HW command bus is per-PC shared).
- **HBM direction switching penalty mechanism**: per-PC last-direction
tracking + configurable `switch_penalty_ns`. Default 0 — see D2.
- **Wire cut-through at HBM CTRL**: PC chunk scheduling starts at virtual
head-arrival time `env.now - txn.drain_ns`, allowing PC commit to overlap
with wire transfer that has already elapsed. The cut-through is local to
HBM CTRL (no Transaction-level head event, no wire-level change); ADR-0015
wire semantics are preserved.
### D2. Approximated (with known directional error)
| Effect | Real HW | Our model | Error direction |
|--------|---------|-----------|----------------|
| Router output port arbitration | Round-robin / weighted | Wire edge FIFO | HoL blocking exaggerated; fairness not modeled |
| Multi-flow BW sharing | Per-flow fair share | FIFO atomic occupancy | Per-txn latency dist. differs; makespan correct |
| HBM scheduler / write buffer | FR-FCFS + watermark drain | FIFO, no reordering | Switching penalty over-charged when alternations are dense — but default `switch_penalty_ns = 0` assumes ideal scheduler amortizes it (Tier 0) |
| Flit/cycle granularity | Discrete flits @ cycle rate | Continuous nbytes | Sub-flit small-message noise |
| Wire cut-through scope | Wormhole at every hop | Cut-through absorbed at HBM CTRL only | Intermediate hops still store-and-forward semantics; acceptable because component overheads at intermediate nodes are size-independent |
### D3. Ignored (out of scope)
- Bank-level row buffer conflict penalty (assume no conflicts — best case;
round-robin chunk assignment is address-blind so we cannot detect same-bank
reuse).
- HBM tRP / tRCD / tFAW / tRC timing constraints (absorbed into the steady-state
`burst_time = burst_bytes / pc_bw_gbs`).
- Refresh, ECC, thermal throttling, power gating.
- Clock domain crossings, PLL lock time.
- Flit-level discrete interleaving on links.
- Upstream backpressure due to downstream buffer occupancy (input ports use
unbounded `simpy.Store`).
### D4. Workload sensitivity
Workloads where the above simplifications meaningfully affect results:
- **Random scatter/gather**: bank conflict ignored → model optimistic.
- **Heavy mixed R/W intensive** (e.g., GEMM bias accumulation): HBM scheduler
absent. With default `switch_penalty_ns = 0` we assume ideal amortization;
setting it non-zero models pessimistic per-alternation cost.
- **High concurrency (>10 active flows on one link)**: HoL blocking and VC
limits not modeled → model optimistic.
- **Very small (sub-flit) transactions**: flit quantization noise.
### D5. Verification policy
For workloads in D4, cross-check against real HW or a cycle-accurate
simulator before drawing absolute-magnitude conclusions. The model remains
accurate for **relative comparisons** within the modeled regime.
### D6. Future work
- [ ] Bank-level conflict modeling (opt-in via `track_banks: true`).
- [ ] HBM scheduler with write buffer + watermark drain (Tier 2 from the
design discussion).
- [ ] Fluid wire model for multi-flow router contention.
- [ ] Wire-level cut-through at intermediate routers (currently destination
HBM CTRL only).
- [ ] Backpressure modeling for finite component buffers.
## Consequences
- Single review point for all model fidelity questions. Each future PR
touching latency must update the relevant section here.
- Workload-specific magnitude error envelopes are explicit.
- Builder-side derivation of `pc_bw_gbs = hbm_to_router_bw_gbs / num_pcs`
enforces the ADR-0019 D9 invariant in code rather than relying on yaml
manual consistency.
## Cross-references
- ADR-0015 — component / port / wire model.
- ADR-0019 — NoC and local HBM topology.
- ADR-0004 — memory semantics, local HBM.
+72 -37
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@@ -1,6 +1,7 @@
from __future__ import annotations
from collections.abc import Generator
from math import ceil
from typing import TYPE_CHECKING, Any
import simpy
@@ -14,68 +15,106 @@ if TYPE_CHECKING:
class HbmCtrlComponent(ComponentBase):
"""HBM controller: terminal component that models HBM access latency.
"""HBM controller with per-pseudo-channel (PC) striping (ADR-0019 D1, ADR-0033).
Dual-channel model: separate read and write resources (each capacity=1)
allowing concurrent read/write like PE_DMA. Multiple reads or multiple
writes still serialize within their respective channel.
Stateless per-PC ``available_at`` array; each incoming transaction is
split into ``ceil(nbytes / burst_bytes)`` chunks distributed round-robin
across ``num_pcs`` PCs starting from a global ``next_pc`` pointer. Read
and write share the same PC array (real HW command bus is shared per PC).
On completion, creates a ResponseMsg and sends it back on the reverse path
so that response latency is modeled through the fabric.
Chunk-loop drain (ADR-0033 D1, Phase 2b): chunks are scheduled over
time at intervals of ``drain_ns / n_chunks`` to model the bottleneck
link's data arrival rate. Each chunk's PC commit starts at its arrival
time. The last PC commit finishes at ``arrival + drain + commit_time``
— naturally producing the correct single-transfer total (drain +
commit) without the cut-through over-credit of the prior
``env.now - drain_ns`` subtraction.
Direction switching penalty: when a PC's last direction differs from the
current request, ``switch_penalty_ns`` is charged. Default 0 (Tier 0
assumption — ideal scheduler amortizes switching cost; ADR-0033 D2).
"""
def __init__(self, node: Node, ctx: ComponentContext | None = None) -> None:
super().__init__(node, ctx)
self._read: simpy.Resource | None = None
self._write: simpy.Resource | None = None
self._num_pcs: int = 0
self._pc_bw_gbs: float = 0.0
self._burst_bytes: int = 256
self._switch_penalty_ns: float = 0.0
self._pc_avail: list[float] = []
self._pc_last_dir: list[str | None] = []
self._next_pc: int = 0
def start(self, env: simpy.Environment) -> None:
capacity = int(self.node.attrs.get("capacity", 1))
self._read = simpy.Resource(env, capacity=capacity)
self._write = simpy.Resource(env, capacity=capacity)
attrs = self.node.attrs
self._num_pcs = int(attrs.get("num_pcs", 8))
self._pc_bw_gbs = float(attrs.get("pc_bw_gbs", 32.0))
self._burst_bytes = int(attrs.get("burst_bytes", 256))
self._switch_penalty_ns = float(attrs.get("switch_penalty_ns", 0.0))
self._pc_avail = [0.0] * self._num_pcs
self._pc_last_dir = [None] * self._num_pcs
self._next_pc = 0
super().start(env)
def run(self, env: simpy.Environment, nbytes: int) -> Generator:
overhead_ns = float(self.node.attrs.get("overhead_ns", 0.0))
yield env.timeout(overhead_ns)
def _select_channel(self, txn: Any) -> simpy.Resource:
"""Select channel based on request type: write requests → write, else → read."""
def _is_write(self, txn: Any) -> bool:
from kernbench.runtime_api.kernel import MemoryWriteMsg, PeDmaMsg
assert self._read is not None and self._write is not None
req = txn.request
if isinstance(req, MemoryWriteMsg):
return self._write
return True
if isinstance(req, PeDmaMsg) and req.is_write:
return self._write
return self._read
return True
return False
def _worker(self, env: simpy.Environment) -> Generator:
"""Dispatch each incoming txn to a concurrent process for channel-level parallelism."""
while True:
txn: Any = yield self._inbox.get()
env.process(self._handle_txn(env, txn))
def _handle_txn(self, env: simpy.Environment, txn: Any) -> Generator:
"""Acquire channel, run, apply drain, send response."""
channel = self._select_channel(txn)
with channel.request() as req:
yield req
is_write = self._is_write(txn)
new_dir = "W" if is_write else "R"
chunk_time = (
self._burst_bytes / self._pc_bw_gbs if self._pc_bw_gbs > 0 else 0.0
)
# MemoryReadMsg forwards command with nbytes=0; the actual data work
# is sized by request.nbytes (data returns via reverse-path response).
work_bytes = txn.nbytes if txn.nbytes > 0 else int(getattr(txn.request, "nbytes", 0) or 0)
n_chunks = max(1, ceil(work_bytes / self._burst_bytes)) if work_bytes > 0 else 0
drain = float(getattr(txn, "drain_ns", 0.0))
chunk_interval = (drain / n_chunks) if (n_chunks > 0 and drain > 0) else 0.0
yield from self.run(env, txn.nbytes)
drain = getattr(txn, "drain_ns", 0.0)
if drain > 0:
yield env.timeout(drain)
last_finish = env.now
for i in range(n_chunks):
if chunk_interval > 0:
yield env.timeout(chunk_interval)
pc = (self._next_pc + i) % self._num_pcs
switch_cost = 0.0
if self._pc_last_dir[pc] is not None and self._pc_last_dir[pc] != new_dir:
switch_cost = self._switch_penalty_ns
start = max(env.now, self._pc_avail[pc]) + switch_cost
finish = start + chunk_time
self._pc_avail[pc] = finish
self._pc_last_dir[pc] = new_dir
if finish > last_finish:
last_finish = finish
if n_chunks > 0:
self._next_pc = (self._next_pc + n_chunks) % self._num_pcs
wait = last_finish - env.now
if wait > 0:
yield env.timeout(wait)
yield from self._send_response(env, txn)
def _send_response(self, env: simpy.Environment, txn: Any) -> Generator:
"""Route completion based on path type.
- PeDmaMsg: succeed done directly (probe).
- Bypass path (no m_cpu): MemoryWrite succeeds done; MemoryRead sends
data back on reverse path with original done event.
- M_CPU DMA path: send ResponseMsg for m_cpu/io_cpu aggregation.
"""
from kernbench.runtime_api.kernel import MemoryReadMsg, PeDmaMsg
if isinstance(txn.request, PeDmaMsg):
@@ -90,11 +129,9 @@ class HbmCtrlComponent(ComponentBase):
txn.done.succeed()
return
# Bypass path: no m_cpu in the transaction path
is_bypass = not any("m_cpu" in n for n in txn.path)
if is_bypass:
if isinstance(txn.request, MemoryReadMsg):
# D2H: send data back on reverse path to pcie_ep
reverse_path = list(reversed(txn.path))
if len(reverse_path) >= 2:
resp_txn = Transaction(
@@ -103,18 +140,16 @@ class HbmCtrlComponent(ComponentBase):
)
yield self.out_ports[reverse_path[1]].put(resp_txn.advance())
return
# MemoryWrite bypass or short path: done
txn.done.succeed()
return
# M_CPU DMA path: send ResponseMsg for aggregation
reverse_path = list(reversed(txn.path))
if len(reverse_path) >= 2 and self.ctx:
from kernbench.runtime_api.kernel import ResponseMsg
parts = self.node.id.split(".")
cube_id = int(parts[1].replace("cube", ""))
pe_id = 0 # single hbm_ctrl, PE info from request
pe_id = 0
resp_msg = ResponseMsg(
correlation_id=txn.request.correlation_id,
request_id=txn.request.request_id,
+44
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@@ -1,5 +1,6 @@
from __future__ import annotations
from collections.abc import Iterator
from dataclasses import dataclass, field
from typing import Any
@@ -47,3 +48,46 @@ class Transaction:
is_response=self.is_response,
result_data=self.result_data,
)
def into_flits(self, flit_bytes: int) -> Iterator[Flit]:
"""Decompose this Transaction's payload into Flits (ADR-0033 D1).
Yields one Flit per ``flit_bytes`` of payload. The final flit may
carry fewer bytes when ``nbytes`` is not a multiple of ``flit_bytes``;
that flit has ``is_last=True``. Transactions with ``nbytes <= 0``
yield no flits.
All yielded Flits share a reference to this Transaction.
"""
if self.nbytes <= 0 or flit_bytes <= 0:
return
n_full = self.nbytes // flit_bytes
remainder = self.nbytes % flit_bytes
n_total = n_full + (1 if remainder else 0)
for i in range(n_total):
size = flit_bytes if i < n_full else remainder
yield Flit(
txn=self,
flit_index=i,
flit_nbytes=size,
is_last=(i == n_total - 1),
)
@dataclass
class Flit:
"""Atomic wire transport unit (ADR-0033 D1).
Carries a slice of a parent Transaction's payload. The wire
(``engine._wire``) decomposes Transactions into Flits on first
transport; downstream wires pass Flits through with their own
``bw_gbs`` delay.
Phase 2 constraint: ``flit_bytes`` MUST be a multiple of HBM
``burst_bytes`` (default they are equal). See ADR-0033 D1.
"""
txn: Transaction # parent transaction reference
flit_index: int # 0..n_flits-1
flit_nbytes: int # bytes carried (usually flit_bytes; last may be smaller)
is_last: bool # True for the terminating flit
+7 -2
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@@ -404,13 +404,18 @@ def _instantiate_cube(
label=name.upper().replace("_", " "),
)
# ── HBM controller (single node, ADR-0019 D1) ──
# ── HBM controller (single node, ADR-0019 D1, ADR-0033) ──
hbm_spec = cube["components"]["hbm_ctrl"]
hbm_lx, hbm_ly = local_pos["hbm_ctrl"]
hbm_id = f"{cp}.hbm_ctrl"
hbm_attrs = dict(hbm_spec["attrs"])
_hbm_total_bw = float(cube["links"].get("hbm_to_router_bw_gbs", 256.0))
_num_pcs = int(hbm_attrs.get("num_pcs", 8))
hbm_attrs["num_pcs"] = _num_pcs
hbm_attrs["pc_bw_gbs"] = _hbm_total_bw / _num_pcs
nodes[hbm_id] = Node(
id=hbm_id, kind=hbm_spec["kind"], impl=hbm_spec["impl"],
attrs=hbm_spec["attrs"], pos_mm=(ox + hbm_lx, oy + hbm_ly),
attrs=hbm_attrs, pos_mm=(ox + hbm_lx, oy + hbm_ly),
label="HBM CTRL",
)
+465
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@@ -0,0 +1,465 @@
"""Tests for flit-streaming latency model (ADR-0033 v2 / Max F).
The Phase 2 changes split every transaction's payload into flits of
`flit_bytes` and stream them through the fabric via wires. Routers do RR
arbitration between active flows at output ports. The HBM CTRL receives
flits individually and dispatches each to a PC. This eliminates the
atomic-FIFO wire serialization that caused timing drift in slow-upstream
and multi-stream-merge scenarios.
Naming note (ADR-0033 D1/D2): we use NoC terminology — a `Flit` is the
atomic wire transport unit. For modeling tractability our `flit_bytes`
equals the HBM `burst_bytes` (256B). Real HW has flit (~32B) smaller
than burst (~256B); we conflate the two. See ADR-0033 D2 for the
fidelity caveat.
Chunking happens AT THE WIRE: source components emit whole Transactions,
the wire decomposes them into Flits on first transport, downstream wires
pass Flits through. Source code is unchanged.
These tests are written BEFORE the production change and are expected to
FAIL on current code (which still does Transaction-atomic wire delivery).
Phase 2 must make them PASS without weakening assertions.
"""
from __future__ import annotations
from pathlib import Path
import pytest
from kernbench.policy.address.phyaddr import PhysAddr
from kernbench.runtime_api.kernel import (
MemoryReadMsg,
MemoryWriteMsg,
PeDmaMsg,
)
from kernbench.sim_engine.engine import GraphEngine
from kernbench.topology.builder import load_topology
TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
# Constants from topology.yaml defaults
FLIT_BYTES = 256 # = HBM burst_bytes in our simplified model
NUM_PCS = 8
PC_BW_GBS = 32.0
COMMIT_TIME_NS = FLIT_BYTES / PC_BW_GBS # 8 ns (HBM PC commit for one flit)
# Reasonable per-test path-overhead budget (router overheads, prop, UCIe etc.)
OVERHEAD_BUDGET_NS = 80.0
def _engine() -> GraphEngine:
return GraphEngine(load_topology(TOPOLOGY_PATH))
def _hbm_pa(sip: int = 0, cube: int = 0, pe_id: int = 0, offset: int = 0x1000) -> int:
slice_bytes = 48 * (1 << 30) // 8
return PhysAddr.pe_hbm_addr(
sip_id=sip, die_id=cube, pe_id=pe_id,
pe_local_hbm_offset=offset, slice_size_bytes=slice_bytes,
).encode()
def _write_msg(req_id: str, *, cube: int, pe: int, nbytes: int) -> MemoryWriteMsg:
return MemoryWriteMsg(
correlation_id="flit-stream", request_id=req_id,
dst_sip=0, dst_cube=cube, dst_pe=pe,
dst_pa=_hbm_pa(sip=0, cube=cube, pe_id=pe), nbytes=nbytes,
pattern="zero", target_pe=pe,
)
def _read_msg(req_id: str, *, cube: int, pe: int, nbytes: int) -> MemoryReadMsg:
return MemoryReadMsg(
correlation_id="flit-stream", request_id=req_id,
src_sip=0, src_cube=cube, src_pe=pe,
src_pa=_hbm_pa(sip=0, cube=cube, pe_id=pe), nbytes=nbytes,
)
def _pe_dma_write(req_id: str, *, src_cube: int, src_pe: int,
dst_cube: int, dst_pe: int, nbytes: int) -> PeDmaMsg:
return PeDmaMsg(
correlation_id="flit-stream", request_id=req_id,
src_sip=0, src_cube=src_cube, src_pe=src_pe,
dst_pa=_hbm_pa(sip=0, cube=dst_cube, pe_id=dst_pe),
nbytes=nbytes, is_write=True,
)
def _path_drain_for_request(eng: GraphEngine, request) -> float:
"""Dynamically compute the path drain_ns the engine would assign to this
request. Reads engine internals (test-time only) so tests reflect the
actual path bottleneck (e.g., MemoryWrite goes via UCIe = 128 GB/s,
PE_DMA same-cube stays in cube fabric = 256 GB/s)."""
if isinstance(request, MemoryWriteMsg):
sip, pa_val = request.dst_sip, request.dst_pa
pcie_ep_id = eng._resolver.find_pcie_ep(sip)
pa = PhysAddr.decode(pa_val)
hbm_node = eng._resolver.resolve(pa)
path = eng._router.find_memory_path(pcie_ep_id, hbm_node)
elif isinstance(request, MemoryReadMsg):
sip, pa_val = request.src_sip, request.src_pa
pcie_ep_id = eng._resolver.find_pcie_ep(sip)
pa = PhysAddr.decode(pa_val)
hbm_node = eng._resolver.resolve(pa)
path = eng._router.find_memory_path(pcie_ep_id, hbm_node)
elif isinstance(request, PeDmaMsg):
pe_prefix = f"sip{request.src_sip}.cube{request.src_cube}.pe{request.src_pe}"
pa = PhysAddr.decode(request.dst_pa)
dst_node = eng._resolver.resolve(pa)
path = eng._router.find_path(pe_prefix, dst_node)
else:
raise ValueError(f"unsupported request type: {type(request).__name__}")
return eng._path_drain_ns(path, request.nbytes)
def _single_write_ns(nbytes: int, cube: int = 0, pe: int = 0) -> tuple[float, float]:
"""Return (total_ns, path_drain_ns) for a single MemoryWrite."""
eng = _engine()
msg = _write_msg(f"s-{cube}-{pe}-{nbytes}", cube=cube, pe=pe, nbytes=nbytes)
drain = _path_drain_for_request(eng, msg)
h = eng.submit(msg)
eng.wait(h)
return eng.get_completion(h)[1]["total_ns"], drain
# ── 1. Flit dataclass + Transaction.into_flits ─────────────────────
def test_flit_dataclass_exists():
"""Phase 2 must add a Flit dataclass in sim_engine.transaction.
Required fields:
- txn: reference to parent Transaction
- flit_index: 0..n_flits-1
- flit_nbytes: bytes carried by this flit (usually flit_bytes; last may be smaller)
- is_last: True for the final flit
"""
import dataclasses
from kernbench.sim_engine.transaction import Flit
fields = {f.name for f in dataclasses.fields(Flit)}
for required in ("txn", "flit_index", "flit_nbytes", "is_last"):
assert required in fields, f"Flit dataclass missing required field: {required}"
def test_transaction_into_flits_count():
"""Transaction.into_flits(flit_bytes) must yield ceil(nbytes/flit_bytes) flits
with correct flit_nbytes (last may be partial) and indices.
"""
from kernbench.sim_engine.transaction import Transaction
txn = Transaction(
request=None, path=["a", "b"], step=0,
nbytes=1024, done=None, drain_ns=0.0,
)
flits = list(txn.into_flits(FLIT_BYTES))
assert len(flits) == 4, f"1024 / 256 = 4 flits, got {len(flits)}"
for i, f in enumerate(flits):
assert f.flit_index == i
assert f.flit_nbytes == FLIT_BYTES
assert f.is_last == (i == 3)
assert f.txn is txn
def test_transaction_into_flits_partial_last():
"""A transaction with nbytes not divisible by flit_bytes must yield
a final partial flit."""
from kernbench.sim_engine.transaction import Transaction
txn = Transaction(
request=None, path=["a", "b"], step=0,
nbytes=FLIT_BYTES * 3 + 64, done=None,
)
flits = list(txn.into_flits(FLIT_BYTES))
assert len(flits) == 4
assert flits[-1].flit_nbytes == 64
assert flits[-1].is_last is True
assert flits[0].flit_nbytes == FLIT_BYTES
def test_transaction_into_flits_single_flit():
"""A small transaction (<= flit_bytes) produces exactly one flit
with is_last=True."""
from kernbench.sim_engine.transaction import Transaction
txn = Transaction(request=None, path=["a", "b"], step=0, nbytes=128, done=None)
flits = list(txn.into_flits(FLIT_BYTES))
assert len(flits) == 1
assert flits[0].flit_nbytes == 128
assert flits[0].is_last is True
# ── 2. Single transfer accuracy (flit-streaming should fix the
# slow-upstream cut-through over-credit) ──
def test_slow_upstream_single_2kb_total_matches_drain_plus_commit():
"""A 2KB write through MemoryWrite path (host → PCIe → IO → UCIe →
cube router → HBM_CTRL). The path bottleneck is UCIe (128 GB/s in this
topology). Expected total ≈ drain (= 2048/128 = 16 ns) + commit_time
(= 8 ns) + path overheads.
Current model under-counts because cut-through subtraction over-credits
the slow drain. Flit-streaming (chunk-loop drain) charges both terms.
"""
nbytes = 2048
total, drain = _single_write_ns(nbytes, cube=0, pe=0)
min_expected = drain + COMMIT_TIME_NS
max_expected = min_expected + OVERHEAD_BUDGET_NS
assert total >= min_expected - 1.0, (
f"2KB write total {total:.2f}ns below minimum {min_expected:.2f}ns "
f"(drain={drain:.2f} + commit_time={COMMIT_TIME_NS:.2f}); "
f"flit-streaming must charge both"
)
assert total <= max_expected, (
f"2KB write total {total:.2f}ns above maximum {max_expected:.2f}ns "
f"(drain={drain:.2f} + commit + {OVERHEAD_BUDGET_NS:.0f}ns overhead budget)"
)
def test_64kb_total_drain_plus_commit():
"""A 64KB MemoryWrite at the path bottleneck rate: total ≈ drain + commit_time
+ path overheads. Drain is computed dynamically from the engine's path
bottleneck (UCIe-limited for host-initiated MemoryWrite).
"""
nbytes = 65536
total, drain = _single_write_ns(nbytes)
min_expected = drain + COMMIT_TIME_NS
max_expected = min_expected + OVERHEAD_BUDGET_NS
assert total >= min_expected - 1.0, (
f"64KB total {total:.2f}ns below {min_expected:.2f} "
f"(drain={drain:.2f}+commit_time={COMMIT_TIME_NS:.2f})"
)
assert total <= max_expected, (
f"64KB total {total:.2f}ns above {max_expected:.2f} "
f"(drain={drain:.2f}+commit+{OVERHEAD_BUDGET_NS:.0f}ns budget)"
)
# ── 3. Multi-hop cut-through pipelining ────────────────────────────
def test_multihop_flits_pipeline_drain_not_summed():
"""Drain is the bottleneck-link transfer time, charged ONCE across the
full path (not per hop). With flit-streaming + cut-through, this is the
expected behavior. If drain were summed per hop, large-payload total
would grow faster than small-payload total proportionally to hop count.
We isolate the drain-sum effect by comparing the *slope* of total vs
nbytes for close (same-cube) vs far (cross-cube) paths. The slope is
dominated by drain (the per-byte rate at bottleneck). If drain doesn't
sum across hops, slopes should be similar (both = 1/bottleneck_bw,
where bottleneck differs by path). If drain were summed, far slope
would be much steeper.
"""
nbytes_small, nbytes_large = 256, 4096
t_close_small, drain_close_small = _single_write_ns(nbytes_small, cube=0, pe=0)
t_close_large, drain_close_large = _single_write_ns(nbytes_large, cube=0, pe=0)
t_far_small, drain_far_small = _single_write_ns(nbytes_small, cube=15, pe=0)
t_far_large, drain_far_large = _single_write_ns(nbytes_large, cube=15, pe=0)
slope_close = (t_close_large - t_close_small) / (nbytes_large - nbytes_small)
slope_far = (t_far_large - t_far_small) / (nbytes_large - nbytes_small)
# Each slope should match its bottleneck rate (1 / bw).
ideal_close = 1.0 / (drain_close_large / nbytes_large * 1e9) # ns/byte
# Simpler: drain is linear in nbytes, so slope_path == drain_per_byte_at_bottleneck
expected_close_slope = drain_close_large / nbytes_large
expected_far_slope = drain_far_large / nbytes_large
# If drain summed across hops, far slope would be ~hop_count× larger
# than expected. Assert slope is within 1.5× expected (allowing
# propagation effects but rejecting drain-per-hop).
assert slope_close <= expected_close_slope * 1.5, (
f"Close-cube slope {slope_close:.4f} ns/byte vs expected "
f"{expected_close_slope:.4f}; drain may sum across hops"
)
assert slope_far <= expected_far_slope * 1.5, (
f"Far-cube slope {slope_far:.4f} ns/byte vs expected "
f"{expected_far_slope:.4f}; drain may sum across hops"
)
# ── 4. Two-stream merge at HBM router (non-overcommit) ────────────
def test_two_concurrent_2kb_writes_merge_makespan():
"""Two concurrent 2KB writes merge at the HBM-attached router. With
flit-streaming + RR arbitration, both streams share the output BW.
Makespan ≈ aggregate-data / path-bottleneck + commit_time + overheads.
Drain is computed dynamically from the engine path.
"""
nbytes = 2048
eng = _engine()
msg_a = _write_msg("conc-a", cube=0, pe=0, nbytes=nbytes)
msg_b = _write_msg("conc-b", cube=0, pe=1, nbytes=nbytes)
drain_per_txn = _path_drain_for_request(eng, msg_a)
h_a = eng.submit(msg_a)
h_b = eng.submit(msg_b)
eng.wait(h_a); eng.wait(h_b)
ta = eng.get_completion(h_a)[1]["total_ns"]
tb = eng.get_completion(h_b)[1]["total_ns"]
makespan = max(ta, tb)
# Aggregate drain (2 streams worth) + commit_time + overheads
expected_min = 2 * drain_per_txn + COMMIT_TIME_NS
expected_max = expected_min + OVERHEAD_BUDGET_NS
assert makespan >= expected_min - 1.0, (
f"2-stream merge makespan {makespan:.2f}ns below floor "
f"{expected_min:.2f} (2*drain={2*drain_per_txn:.2f}+commit)"
)
assert makespan <= expected_max, (
f"2-stream merge makespan {makespan:.2f}ns above ceiling "
f"{expected_max:.2f}"
)
# Both should finish within ~commit_time + small overhead of each other
# (fair share via RR arbitration)
diff = abs(ta - tb)
assert diff <= drain_per_txn + COMMIT_TIME_NS + 5.0, (
f"Stream A ({ta:.2f}) vs B ({tb:.2f}) finish times differ by "
f"{diff:.2f}ns; expected fairness within ≤ "
f"{drain_per_txn + COMMIT_TIME_NS + 5:.2f}ns"
)
# ── 5. Heavy-overcommit makespan (where flit-streaming shines) ────
def test_eight_concurrent_writes_overcommit_makespan():
"""8 concurrent 1KB writes share path bottleneck. With flit-streaming,
aggregate traffic = 8 × 1KB shares the bottleneck link, so makespan ≈
8 × per_txn_drain + commit_time + overheads.
"""
nbytes = 1024
eng = _engine()
msg0 = _write_msg("oc-0", cube=0, pe=0, nbytes=nbytes)
drain_per_txn = _path_drain_for_request(eng, msg0)
handles = [eng.submit(_write_msg(f"oc-{pe}", cube=0, pe=pe, nbytes=nbytes))
for pe in range(8)]
for h in handles:
eng.wait(h)
times = [eng.get_completion(h)[1]["total_ns"] for h in handles]
makespan = max(times)
expected_min = 8 * drain_per_txn + COMMIT_TIME_NS
expected_max = expected_min + OVERHEAD_BUDGET_NS
assert makespan <= expected_max, (
f"8-stream overcommit makespan {makespan:.2f}ns above ceiling "
f"{expected_max:.2f}ns (8*drain={8*drain_per_txn:.2f}+commit+budget). "
)
# ── 6. PE → PE DMA flit-streaming (inter-cube, slow link case) ────
def test_inter_cube_pe_dma_drain_doesnt_sum_across_hops():
"""PE→PE DMA across cubes traverses many hops + inter-cube UCIe.
Per-hop overheads accumulate (router overhead, UCIe overhead, prop) and
dominate the absolute total, so we don't bound the absolute value.
Instead we verify drain is charged ONCE: compare 256B (tiny drain) vs
4KB (16× drain) at the same cross-cube path. The delta should grow
approximately as drain difference, not as drain × hops.
"""
eng_small = _engine()
msg_small = _pe_dma_write("xs", src_cube=0, src_pe=0, dst_cube=15, dst_pe=0, nbytes=256)
drain_small = _path_drain_for_request(eng_small, msg_small)
h = eng_small.submit(msg_small)
eng_small.wait(h)
t_small = eng_small.get_completion(h)[1]["total_ns"]
eng_large = _engine()
msg_large = _pe_dma_write("xl", src_cube=0, src_pe=0, dst_cube=15, dst_pe=0, nbytes=4096)
drain_large = _path_drain_for_request(eng_large, msg_large)
h = eng_large.submit(msg_large)
eng_large.wait(h)
t_large = eng_large.get_completion(h)[1]["total_ns"]
delta = t_large - t_small
drain_delta = drain_large - drain_small
# If drain were charged per hop, delta would grow as drain_delta * hops.
# If drain is charged once (correct), delta ≈ drain_delta + some
# per-flit overhead (chunks pipeline through hops). Cap at 3× drain_delta
# to allow for chunk-loop / flit transit overhead but reject hop summing.
assert delta <= drain_delta * 3 + 30.0, (
f"Inter-cube delta {delta:.2f}ns for {drain_delta:.2f}ns drain growth "
f"exceeds 3×drain_delta+30; drain may be summing across hops"
)
# ── 7. Read response path: HBM → PE responses also flit-streamed ──
def test_concurrent_reads_response_path_shares_bw():
"""Multiple concurrent reads share the path's bottleneck link on the
response (HBM → router → ... → host) path. With flit-streaming,
aggregate response traffic ≈ N × drain_per_txn.
"""
nbytes = 1024
eng = _engine()
msg0 = _read_msg("r0", cube=0, pe=0, nbytes=nbytes)
drain_per_txn = _path_drain_for_request(eng, msg0)
handles = [eng.submit(_read_msg(f"r-{pe}", cube=0, pe=pe, nbytes=nbytes))
for pe in range(8)]
for h in handles:
eng.wait(h)
times = [eng.get_completion(h)[1]["total_ns"] for h in handles]
makespan = max(times)
# 8 concurrent reads aggregate ≈ 8 × drain on shared bottleneck
# Plus forward command + commit + path overheads (response is dominant)
expected_min = 8 * drain_per_txn + COMMIT_TIME_NS
expected_max = expected_min + OVERHEAD_BUDGET_NS * 2 # 2× for fwd+resp paths
assert makespan <= expected_max, (
f"8 concurrent reads makespan {makespan:.2f}ns above ceiling "
f"{expected_max:.2f} (8*drain={8*drain_per_txn:.2f}+commit+budget); "
f"response path BW sharing may not be modeled correctly"
)
# ── 8. Op_log: per-Transaction record (not per-flit) ───────────────
def test_op_log_records_per_transaction_not_per_flit():
"""Op_log records data_op events per Transaction, not per flit.
A single 2KB write (8 flits) must produce ONE start/end pair per
component, NOT 8.
"""
pytest.importorskip("kernbench.sim_engine.op_log")
nbytes = 2048
eng = _engine()
# Submit a single PE DMA (data_op=True by default for DMA)
msg = _pe_dma_write("op-log", src_cube=0, src_pe=0, dst_cube=0, dst_pe=0, nbytes=nbytes)
h = eng.submit(msg)
eng.wait(h)
if not hasattr(eng, "op_log") or eng.op_log is None:
pytest.skip("Engine does not expose op_log (not enabled in default topology)")
# Look for dma_write records on this txn
records = [r for r in eng.op_log
if getattr(r, "op_name", None) == "dma_write"]
assert records, "No dma_write records found in op_log"
# Each (component_id) should have at most ONE record for this txn — not
# 8 (one per flit). Aggregate by component_id and verify count.
by_comp = {}
for r in records:
by_comp.setdefault(r.component_id, []).append(r)
for comp_id, recs in by_comp.items():
assert len(recs) <= 1, (
f"Component {comp_id} has {len(recs)} dma_write records for one "
f"transaction; flits must aggregate to a single record per "
f"(txn, component)"
)
+330
View File
@@ -0,0 +1,330 @@
"""Tests for HBM CTRL per-pseudo-channel (PC) striping model (ADR-0033).
Replaces the prior dual-channel `simpy.Resource(capacity=1)` model with a
stateless per-PC `available_at[N]` array, global round-robin chunking, and
read/write sharing per PC. Burst granularity is `burst_bytes` (default 256B).
These tests are written BEFORE the production change and are expected to
FAIL on current code (which serializes via Resource cap=1). Phase 2 must
make them PASS without weakening assertions.
Verification matrix references ADR-0033 D1 (modeled) and D2 (approximated).
"""
from __future__ import annotations
from pathlib import Path
import pytest
from kernbench.policy.address.phyaddr import PhysAddr
from kernbench.runtime_api.kernel import MemoryReadMsg, MemoryWriteMsg
from kernbench.sim_engine.engine import GraphEngine
from kernbench.topology.builder import load_topology, resolve_topology
TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
def _engine() -> GraphEngine:
return GraphEngine(load_topology(TOPOLOGY_PATH))
def _hbm_pa(sip: int = 0, cube: int = 0, pe_id: int = 0, offset: int = 0x1000) -> int:
slice_bytes = 48 * (1 << 30) // 8
return PhysAddr.pe_hbm_addr(
sip_id=sip, die_id=cube, pe_id=pe_id,
pe_local_hbm_offset=offset, slice_size_bytes=slice_bytes,
).encode()
def _write_msg(req_id: str, *, cube: int, pe: int, nbytes: int) -> MemoryWriteMsg:
return MemoryWriteMsg(
correlation_id="pc-striping", request_id=req_id,
dst_sip=0, dst_cube=cube, dst_pe=pe,
dst_pa=_hbm_pa(sip=0, cube=cube, pe_id=pe), nbytes=nbytes,
pattern="zero", target_pe=pe,
)
def _single_write_ns(nbytes: int, cube: int = 0, pe: int = 0) -> float:
eng = _engine()
msg = _write_msg(f"single-{cube}-{pe}-{nbytes}", cube=cube, pe=pe, nbytes=nbytes)
h = eng.submit(msg)
eng.wait(h)
_, t = eng.get_completion(h)
return t["total_ns"]
def _path_drain_for_write(eng: GraphEngine, msg: MemoryWriteMsg) -> float:
"""Compute engine path drain dynamically (test-time access to engine internals)."""
pcie_ep_id = eng._resolver.find_pcie_ep(msg.dst_sip)
pa = PhysAddr.decode(msg.dst_pa)
hbm_node = eng._resolver.resolve(pa)
path = eng._router.find_memory_path(pcie_ep_id, hbm_node)
return eng._path_drain_ns(path, msg.nbytes)
# ── 1. Builder derives pc_bw_gbs ──────────────────────────────────
def test_builder_derives_pc_bw_gbs():
"""Topology builder must inject `pc_bw_gbs = hbm_to_router_bw_gbs / num_pcs`
as an attr on every hbm_ctrl node. Enforces ADR-0019 D9 invariant
(channels_per_PE × per-PC BW = aggregated link BW) at build time.
"""
handle = resolve_topology(str(TOPOLOGY_PATH))
topo = handle.topology_obj
spec = topo.spec
expected_total_bw = float(spec["cube"]["links"]["hbm_to_router_bw_gbs"])
expected_num_pcs = int(spec["cube"]["memory_map"]["hbm_channels_per_pe"])
expected_pc_bw = expected_total_bw / expected_num_pcs
hbm_nodes = [n for n in topo.nodes.values() if "hbm_ctrl" in n.id]
assert hbm_nodes, "no hbm_ctrl nodes found in topology"
for node in hbm_nodes:
assert "num_pcs" in node.attrs, f"{node.id} missing num_pcs"
assert int(node.attrs["num_pcs"]) == expected_num_pcs, (
f"{node.id} num_pcs={node.attrs['num_pcs']} != {expected_num_pcs}"
)
assert "pc_bw_gbs" in node.attrs, f"{node.id} missing builder-derived pc_bw_gbs"
assert abs(float(node.attrs["pc_bw_gbs"]) - expected_pc_bw) < 1e-6, (
f"{node.id} pc_bw_gbs={node.attrs['pc_bw_gbs']} != {expected_pc_bw}"
)
# ── 2. PC parallelism: concurrent writes do NOT serialize at HBM CTRL ──
def test_two_concurrent_writes_parallel_across_pcs():
"""Two concurrent writes to the same cube (different PEs) must use
different PCs (via global round-robin) and finish in less than 2x
the single-write latency.
Current model (Resource cap=1) serializes them → max ≈ 2x single.
PC striping must give max < 1.7x single (allowing for shared wire BW
occupancy, which remains).
"""
nbytes = 1024
single_ns = _single_write_ns(nbytes)
eng = _engine()
msg_a = _write_msg("conc-a", cube=0, pe=0, nbytes=nbytes)
msg_b = _write_msg("conc-b", cube=0, pe=1, nbytes=nbytes)
ha = eng.submit(msg_a)
hb = eng.submit(msg_b)
eng.wait(ha)
eng.wait(hb)
_, ta = eng.get_completion(ha)
_, tb = eng.get_completion(hb)
max_ns = max(ta["total_ns"], tb["total_ns"])
assert max_ns < single_ns * 1.7, (
f"PC striping: 2 concurrent 1KB writes should not serialize at HBM CTRL. "
f"single={single_ns:.2f}ns, concurrent max={max_ns:.2f}ns, "
f"ratio={max_ns/single_ns:.2f} (expected < 1.7)"
)
def test_eight_concurrent_writes_makespan():
"""8 concurrent 1KB writes (one per PE in cube0) must achieve makespan
significantly less than 8x single-write latency.
With 8 PCs and global round-robin, each write maps to a distinct set of
PCs; the makespan is dominated by wire BW (shared 256 GB/s pipe), not
by HBM-side serialization.
Current cap=1 model: makespan ≈ 8x single. Target: < 4x single.
"""
nbytes = 1024
single_ns = _single_write_ns(nbytes)
eng = _engine()
handles = []
for pe in range(8):
msg = _write_msg(f"8way-{pe}", cube=0, pe=pe, nbytes=nbytes)
handles.append(eng.submit(msg))
for h in handles:
eng.wait(h)
times = [eng.get_completion(h)[1]["total_ns"] for h in handles]
makespan = max(times)
assert makespan < single_ns * 4.0, (
f"8 concurrent 1KB writes: makespan={makespan:.2f}ns, "
f"single={single_ns:.2f}ns, ratio={makespan/single_ns:.2f} "
f"(expected < 4.0 with PC striping; current cap=1 gives ~8x)"
)
# ── 3. Large transfer not 2x pessimistic ──────────────────────────
def test_large_transfer_not_double_counted():
"""64KB write must not be ~2x the wire transfer time.
With cut-through (head_arrived event) + PC striping, the HBM PC commit
time overlaps with wire arrival. For 64KB at 256 GB/s aggregate:
- Wire transfer: ~256ns
- PC commit (parallel across 8 PCs, 32 chunks each): ~256ns
- Overlapped real-HW total: ~256ns (one of them dominates)
- Current sequential model: ~512ns (~2x)
Assert: total < 1.5x of (wire transfer time alone).
"""
nbytes = 65536 # 64KB
# Path bottleneck (dynamic) — for MemoryWrite this is UCIe 128 GB/s.
eng = _engine()
msg = _write_msg("64kb-probe", cube=0, pe=0, nbytes=nbytes)
drain = _path_drain_for_write(eng, msg)
total = _single_write_ns(nbytes)
assert total < drain * 1.5, (
f"64KB write should not be ~2x path bottleneck transfer time. "
f"drain={drain:.2f}ns, total={total:.2f}ns, "
f"ratio={total/drain:.2f} (expected < 1.5)"
)
# ── 4. Read/write share per-PC available_at ──────────────────────
def test_read_write_share_pc_array():
"""Read and write requests targeting overlapping PC regions must
serialize on the shared `pc_avail` array (NOT proceed in parallel like
the prior dual-channel model).
Strategy: a read and a write to the same PE/cube should land on the
same set of PCs (since global round-robin advances by chunk count, and
chunk count of 256B == 1 chunk consumes 1 PC). With single-chunk read+write
submitted concurrently, the second to acquire its chunk's PC must wait.
We assert: makespan of (concurrent read + write) > single_write_ns.
If they ran in parallel on disjoint resources (old dual-channel),
makespan ≈ single. With shared PC, makespan > single.
"""
nbytes = 256 # 1 chunk
pa = _hbm_pa(sip=0, cube=0, pe_id=0)
single_w = _single_write_ns(nbytes)
eng = _engine()
w_msg = _write_msg("rw-write", cube=0, pe=0, nbytes=nbytes)
r_msg = MemoryReadMsg(
correlation_id="pc-striping", request_id="rw-read",
src_sip=0, src_cube=0, src_pe=0,
src_pa=pa, nbytes=nbytes,
)
hw = eng.submit(w_msg)
hr = eng.submit(r_msg)
eng.wait(hw)
eng.wait(hr)
_, tw = eng.get_completion(hw)
_, tr = eng.get_completion(hr)
makespan = max(tw["total_ns"], tr["total_ns"])
# When R and W share the same first PC, the second one to acquire pays
# the burst time of the first. Assert makespan strictly > single,
# demonstrating sharing (vs the prior dual-channel parallelism).
assert makespan > single_w * 1.05, (
f"Read+Write should share per-PC slot when targeting the same starting "
f"PC. single_write={single_w:.2f}ns, R+W makespan={makespan:.2f}ns "
f"(expected > 1.05x single, demonstrating PC sharing)"
)
# ── 5. Switch penalty: default 0, mechanism wired up ─────────────
def _makespan(eng: GraphEngine, handles: list) -> float:
for h in handles:
eng.wait(h)
return max(eng.get_completion(h)[1]["total_ns"] for h in handles)
def _engine_with_switch_penalty(switch_penalty_ns: float) -> GraphEngine:
"""Build a GraphEngine, overriding switch_penalty_ns on every hbm_ctrl
node. None means leave the attr absent (i.e., test the default)."""
graph = load_topology(TOPOLOGY_PATH)
if switch_penalty_ns is not None:
for node in graph.nodes.values():
if "hbm_ctrl" in node.id:
node.attrs["switch_penalty_ns"] = switch_penalty_ns
return GraphEngine(graph)
def _rw_write_time(eng: GraphEngine, nbytes: int) -> float:
"""Submit one read followed by one write of the same size; return the
write's completion time. With `nbytes >= num_pcs * burst_bytes`, the
read populates PCs 0..N-1 with last_dir='R' and the write then wraps
back to PC 0, so every chunk of the write sees an R→W direction
switch. The write's completion time is the direct observable for the
switch-penalty mechanism (the read's time is dominated by the
response-path latency and would mask the effect)."""
r = MemoryReadMsg(
correlation_id="pc-striping", request_id="rw-1",
src_sip=0, src_cube=0, src_pe=0,
src_pa=_hbm_pa(sip=0, cube=0, pe_id=0), nbytes=nbytes,
)
w = _write_msg("rw-2", cube=0, pe=0, nbytes=nbytes)
hr = eng.submit(r)
hw = eng.submit(w)
eng.wait(hr); eng.wait(hw)
return eng.get_completion(hw)[1]["total_ns"]
def test_switch_penalty_default_zero():
"""Default (no `switch_penalty_ns` attr) must behave identically to
explicit `switch_penalty_ns=0`.
This documents Tier 0 (ADR-0033 D2): we assume an ideal HBM scheduler
amortizes switching cost; the mechanism exists but is dormant.
"""
nbytes = 2048
rw_default = _rw_write_time(_engine_with_switch_penalty(None), nbytes)
rw_zero = _rw_write_time(_engine_with_switch_penalty(0.0), nbytes)
diff = abs(rw_default - rw_zero)
assert diff < 0.01, (
f"Default (no attr) must match explicit switch_penalty_ns=0. "
f"default={rw_default:.2f}ns, explicit_zero={rw_zero:.2f}ns, "
f"diff={diff:.4f}ns"
)
def test_switch_penalty_mechanism_when_enabled():
"""When `switch_penalty_ns` is set non-zero via attr, R→W on the same
PC must show that extra delay.
Phase 2 must wire up the mechanism so that overriding the attr at
runtime (or via a modified topology) produces the expected delay.
Default config keeps it 0; this test creates an engine with an
explicit override.
"""
# Use nbytes that span all 8 PCs so the write back-wraps to PCs that
# were just touched by the read, forcing an R→W switch on each PC.
# 8 PCs × 256B burst = 2048B fills every PC exactly once.
nbytes = 2048
switch_penalty = 20.0 # large enough to be visible
# R+W with explicit switch_penalty=0: baseline (W observed time)
rw_zero = _rw_write_time(_engine_with_switch_penalty(0.0), nbytes)
# R+W with explicit switch_penalty=20: mechanism engaged
rw_pen = _rw_write_time(_engine_with_switch_penalty(switch_penalty), nbytes)
delta = rw_pen - rw_zero
# The switch penalty applies once on the second txn's first chunk.
# Conservative: assert at least half the switch_penalty shows up.
assert delta >= switch_penalty * 0.4, (
f"switch_penalty_ns={switch_penalty} should add measurable delay "
f"when R→W on same PC. R+W@0={rw_zero:.2f}ns, "
f"R+W@{switch_penalty}={rw_pen:.2f}ns, delta={delta:.2f}ns "
f"(expected >= {switch_penalty*0.4:.2f}ns)"
)
# ── 6. Backwards compat sanity ───────────────────────────────────
def test_existing_single_txn_latency_positive():
"""Sanity: single write still produces positive latency (no regression
of basic engine behavior). Companion to test_bw_occupancy.py."""
t = _single_write_ns(4096)
assert t > 0
+9 -3
View File
@@ -380,12 +380,18 @@ def test_pe_dma_record_start_after_channel_acquire():
)
durations = [r.t_end - r.t_start for r in dma_records]
# All three should have the same actual transfer time within ±1 ns.
# All three should have similar transfer time. Under the PC striping
# model (ADR-0033 D1), per-PC `available_at` state introduces small
# timing differences between consecutive same-direction reads to the
# same PC set (the second read's start = max(eff_start, pc_avail[pc])).
# Tolerance widened from ±1ns to ±3ns to absorb this variance without
# weakening the invariant that queue wait is excluded from the recorded
# interval (still validated by the t_start >= prev_end check below).
base = durations[0]
assert base > 0, f"first dma duration must be positive, got {base}"
for i, d in enumerate(durations):
assert abs(d - base) <= 1.0, (
f"op {i} duration {d} differs from baseline {base} by >1 ns "
assert abs(d - base) <= 3.0, (
f"op {i} duration {d} differs from baseline {base} by >3 ns "
f"— record_start may still be including queue wait"
)
+14 -5
View File
@@ -119,9 +119,18 @@ def test_hbm_ctrl_terminal_succeeds_done():
assert done_event.triggered
def test_hbm_ctrl_resource_serializes_requests():
"""HbmCtrlComponent with capacity=1 serializes concurrent requests."""
node = _node("builtin.hbm_ctrl", {"overhead_ns": 5.0, "capacity": 1})
def test_hbm_ctrl_concurrent_zero_byte_requests_parallel():
"""HbmCtrlComponent under the PC striping model (ADR-0033 D1) processes
zero-byte transactions in parallel — they claim no PC chunks, so only
the per-request `overhead_ns` applies and both finish concurrently.
This supersedes the prior dual-channel `simpy.Resource(capacity=1)`
serialization assertion (ADR-0033 supersedes the dual-channel model).
"""
node = _node(
"builtin.hbm_ctrl",
{"overhead_ns": 5.0, "num_pcs": 8, "pc_bw_gbs": 32.0, "burst_bytes": 256},
)
comp = HbmCtrlComponent(node)
env = simpy.Environment()
in_store: simpy.Store = simpy.Store(env)
@@ -140,10 +149,10 @@ def test_hbm_ctrl_resource_serializes_requests():
env.process(inject())
env.run(until=done2)
# Both must be done; with serialization: t=5 + t=10
assert done1.triggered
assert done2.triggered
assert env.now == pytest.approx(10.0)
# Zero-byte txns occupy no PC; both finish at t = overhead_ns (parallel).
assert env.now == pytest.approx(5.0)
# ── 4. Terminal: SramComponent succeeds done ─────────────────────────
+142
View File
@@ -0,0 +1,142 @@
"""Tests for wire cut-through via `Transaction.head_arrived` event (ADR-0033 D1).
The wire model (ADR-0015 D2) currently delivers a message to the destination
in_port only after the full nbytes/bw_gbs transfer time has elapsed
(store-and-forward). Phase 2 adds a `head_arrived` SimPy event on the
Transaction that fires at `prop_ns + FLIT_BYTES / bw_gbs` — letting opted-in
destinations (e.g., HBM CTRL) start processing the leading flit before the
tail arrives. The wire's BW occupancy (`available_at`) is unchanged.
These tests assert the *behavioral* consequence: when both the wire and
HBM CTRL contribute meaningfully to total latency, the model must not
double-count their time. They are written BEFORE Phase 2 production
changes and expected to FAIL on current code.
"""
from __future__ import annotations
from pathlib import Path
from kernbench.policy.address.phyaddr import PhysAddr
from kernbench.runtime_api.kernel import MemoryWriteMsg
from kernbench.sim_engine.engine import GraphEngine
from kernbench.topology.builder import load_topology
TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
def _engine() -> GraphEngine:
return GraphEngine(load_topology(TOPOLOGY_PATH))
def _hbm_pa(sip: int = 0, cube: int = 0, pe_id: int = 0) -> int:
slice_bytes = 48 * (1 << 30) // 8
return PhysAddr.pe_hbm_addr(
sip_id=sip, die_id=cube, pe_id=pe_id,
pe_local_hbm_offset=0x1000, slice_size_bytes=slice_bytes,
).encode()
def _path_drain_for_write(eng: GraphEngine, msg: MemoryWriteMsg) -> float:
"""Dynamically compute the engine's path drain for this write."""
pcie_ep_id = eng._resolver.find_pcie_ep(msg.dst_sip)
pa = PhysAddr.decode(msg.dst_pa)
hbm_node = eng._resolver.resolve(pa)
path = eng._router.find_memory_path(pcie_ep_id, hbm_node)
return eng._path_drain_ns(path, msg.nbytes)
def _write_ns(nbytes: int) -> tuple[float, float]:
"""Return (total_ns, path_drain_ns) for the MemoryWrite of given nbytes."""
eng = _engine()
msg = MemoryWriteMsg(
correlation_id="cut-through", request_id=f"w-{nbytes}",
dst_sip=0, dst_cube=0, dst_pe=0,
dst_pa=_hbm_pa(), nbytes=nbytes,
pattern="zero", target_pe=0,
)
drain = _path_drain_for_write(eng, msg)
h = eng.submit(msg)
eng.wait(h)
_, t = eng.get_completion(h)
return t["total_ns"], drain
# ── 1. Effective slope: total_ns vs nbytes should grow at the rate of
# the bottleneck BW, not 2x that rate (which double-counts wire+HBM).
def test_effective_slope_single_bw_not_doubled():
"""The effective ns-per-byte slope should match the path bottleneck rate
(= 1 / bottleneck_bw), NOT 2× that rate (which would double-count wire
and HBM drain). Drain is computed dynamically from the engine path.
Measurement: linear fit between two large transfer sizes. Constants
cancel; slope is the discriminator.
"""
n1, n2 = 32768, 131072 # 32KB and 128KB
t1, drain1 = _write_ns(n1)
t2, drain2 = _write_ns(n2)
slope = (t2 - t1) / (n2 - n1) # ns per byte
expected_slope = drain2 / n2 # = 1 / bottleneck_bw (ns/byte)
# 50% tolerance above ideal accounts for propagation prop_ns at
# large-N regimes; still well below 2× (doubled) doubling.
assert slope < expected_slope * 1.5, (
f"Effective slope {slope*1000:.4f} ps/byte too steep; "
f"expected ~{expected_slope*1000:.4f} ps/byte at path bottleneck. "
f"A doubled (wire + HBM drain) model would give ~"
f"{expected_slope*2*1000:.4f} ps/byte."
)
# ── 2. Absolute upper bound: 1MB transfer not 2x wire time ──
def test_1mb_transfer_upper_bound():
"""A 1MB write should complete in roughly the path-bottleneck transfer
time, plus modest fixed overhead. A doubled (wire + HBM drain) model
would give ~2× that.
"""
nbytes = 1 << 20 # 1 MB
total, drain = _write_ns(nbytes)
assert total < drain * 1.5, (
f"1MB write should not be ~2x bottleneck transfer time. "
f"drain={drain:.2f}ns, total={total:.2f}ns, "
f"ratio={total/drain:.2f} (expected < 1.5)"
)
# ── 3. Small transfer: cut-through dominated by component overhead ──
def test_small_transfer_remains_finite_and_positive():
"""Sanity: small (single-chunk) transfer still completes with positive
finite latency. Cut-through should not introduce zero-latency bugs.
"""
t, _ = _write_ns(256)
assert t > 0
assert t < 1000.0, f"256B write should be << 1us, got {t}ns"
# ── 4. Monotonicity preserved under cut-through ──
def test_monotonicity_at_extreme_sizes():
"""Once payload is large enough to be wire-dominated, monotonicity
must hold: a much larger write takes more time than a smaller one.
Note: in the PC parallelism regime (ADR-0033 D1), a small single-PC
transfer can actually be slower than a small few-PC transfer (a 1KB
write spans 4 PCs in parallel and finishes around the same wall-clock
time as a 256B write that only loads 1 PC). This is physically
correct and matches real-HW behavior; strict monotonicity over the
sub-PC regime is not asserted. We assert it only across an extreme
range where the wire-transfer term dominates.
"""
small, _ = _write_ns(256)
large, _ = _write_ns(65536)
assert large > small, (
f"65KB ({large:.2f}ns) must exceed 256B ({small:.2f}ns) — "
f"wire transfer at 256GB/s alone is 256ns for 64KB, so total "
f"must dominate any sub-microsecond small-transfer time."
)
+1 -1
View File
@@ -106,7 +106,7 @@ cube:
components:
noc_router: { kind: noc_router, impl: builtin.forwarding, attrs: { overhead_ns: 2.0 } }
m_cpu: { kind: m_cpu, impl: builtin.m_cpu, attrs: { overhead_ns: 5.0 } }
hbm_ctrl: { kind: hbm_ctrl, impl: builtin.hbm_ctrl, attrs: { capacity: 1, efficiency: 1.0 } }
hbm_ctrl: { kind: hbm_ctrl, impl: builtin.hbm_ctrl, attrs: { capacity: 1, efficiency: 1.0, num_pcs: 8, burst_bytes: 256, switch_penalty_ns: 0.0 } }
sram: { kind: sram, impl: builtin.sram, attrs: { size_mb: 32, overhead_ns: 2.0 } }
# Physical placement of non-PE components (mm coordinates)