ywkang 3647e2d8f5 gqa(adr): ADR-0064/0065 second-pass review — 1024B rationale, FIFO as ordering source, robust formula-based tests, D5/D6 auto-bind alignment
ADR-0064 Revision 2 second-pass review fixes:
- D7 added 1024-byte cap rationale: explicitly framed as a *safe
  engineering limit* (intentionally above all known composites at ~322
  bytes, finite descriptor capacity placeholder), not a measured HW
  number. Default is the discipline; topology override for real HW.
- D7 segment ordering: strict FIFO is the *ordering source*; rw_handles
  is dependency metadata, not the ordering primitive. Explicit note for
  the future RW-aware reorder migration path.
- Tests rewritten around the formula (D1) instead of specific numbers:
  - Test #1 → "formula preservation" (parametrized across composites,
    asserts dispatch == FIXED + bytes × R, not anchor 43 ns).
  - Test #2 → robust "opt3 > 2 × opt2" qualitative gate; ≈ 4.0× is
    informative only, not the gate, so calibration changes don't break.
  - Test #9 → qualitative (opt2 < opt3 at all R), not a numeric ratio.
- Anchor description in D3 stays as *informative* (shows the model
  produces ≈ 43 ns at defaults), but is no longer a test gate.

ADR-0065 second-pass review:
- D5 step 5 aligned with D6.6 invariant: explicit conflict check before
  auto-binding (previously written as if auto-bind always happens).
  Mirrors D6.6 wording: error if both kernel explicit `a` and prologue
  primary_out are present.
- Test #7 made robust: `opt3 > 2 × opt2` gate (was ≈ 4.0×).
  Default-calibration model expectation (≈ 4.0×) recorded as informative
  reference, not the gate.

DDD-0065 follow-on robust thresholds:
- §1.4 success criteria: ratio condition rewritten as `opt3 > 2 × opt2`
  with model-expected ≈ 4.0× as informative.
- §9 P6 phase gate: `opt3 > 2 × opt2` (was 4.0× ± 15%).
- §10 dispatch ratio test: assert `opt3 > 2 × opt2`; record observed
  ratio for performance tracking but do not gate on it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-10 16:34:34 -07:00
2026-03-18 11:47:48 -07:00
2026-03-18 11:47:48 -07:00

kernbench

A discrete-event simulator for AI accelerator hardware, built on SimPy. It models the full data path — from host PCIe injection through IO chiplet, NOC mesh, crossbar, and HBM — to measure end-to-end latency with contention and queueing.

Architecture

Host (CLI)
  |
  +-- kernbench run     -> run a benchmark (QKV GEMM, AllReduce, ...)
  +-- kernbench probe   -> latency/BW analysis for predefined traffic patterns
  |
  v
+---------------------------------------------------+
|  Runtime API          (runtime_api/)              |
|  MemoryWriteMsg, MemoryReadMsg, PeDmaMsg,         |
|  KernelLaunchMsg                                  |
+---------------------------------------------------+
|  Simulation Engine    (sim_engine/)               |
|  SimPy processes, wire model, BW occupancy        |
+---------------------------------------------------+
|  Components           (components/)               |
|  pcie_ep, io_cpu, m_cpu, noc, xbar, hbm_ctrl,    |
|  pe_cpu, pe_dma, pe_gemm, pe_math, pe_tcm, ...   |
+---------------------------------------------------+
|  Topology             (topology/)                 |
|  YAML-driven graph: 4x4 cube mesh, UCIe links,   |
|  IO chiplet with NOC, HBM slices                  |
+---------------------------------------------------+

Prerequisites

  • Python 3.10+
  • Dependencies: simpy, pyyaml, pytest

Installation

# Create virtual environment
python -m venv .venv

# Activate (Windows)
.venv\Scripts\activate

# Activate (Linux/macOS)
source .venv/bin/activate

# Install in editable mode
pip install -e ".[dev]"

Usage

Probe — Latency and Bandwidth Analysis

The probe command runs predefined traffic patterns (H2D write, D2H read, PE DMA) and reports latency breakdown, bottleneck bandwidth, and utilization.

# Run all probe cases
kernbench probe --topology topology.yaml

# Run a specific case
kernbench probe --topology topology.yaml --case pe-local-hbm

Output includes:

  • Summary tables — actual latency, overhead/drain/wire breakdown, effective BW, utilization
  • BW saturation sweep — utilization at 4KB through 1MB to show saturation threshold
  • Per-hop route traces — cumulative timestamps at every node along the path

Run — Execute a Benchmark

# Run a benchmark on all devices
kernbench run --topology topology.yaml --bench qkv_gemm

# Run on a specific device
kernbench run --topology topology.yaml --bench qkv_gemm --device sip:0

Available benchmarks (in benches/):

  • qkv_gemm — single-PE QKV GEMM
  • qkv_gemm_multi_pe — multi-PE QKV GEMM
  • ipcq_allreduce — IPCQ AllReduce

Tests

# Run all tests (278 tests)
pytest

# Run a specific test file
pytest tests/test_probe.py -v

# Run a single test
pytest tests/test_probe.py::test_h2d_latency_monotonic -v

# Run with output shown
pytest -s tests/test_probe.py

Key test files:

File Coverage
test_probe.py Probe latency invariants, monotonicity, determinism, BW sweep
test_engine.py SimPy engine: submit/wait/complete, routing, multi-SIP
test_bw_occupancy.py Wire BW contention, HOL blocking, back-to-back serialization
test_iochiplet_noc_d2h.py IO chiplet NOC topology, H2D/D2H data paths
test_noc_mesh.py 2D mesh NOC routing, Manhattan distance
test_pe_components.py PE-internal components: cpu, scheduler, dma, gemm
test_routing.py XY routing, address resolution, path finding
test_topology_compile.py YAML topology compilation, node/edge validation

Topology Configuration

The system is configured via topology.yaml. Key parameters:

Parameter Default Description
ns_per_mm 0.01 Wire propagation delay (10 ps/mm)
cube_mesh 4x4 Cube grid dimensions per SIP
ucie.overhead_ns 8.0 UCIe protocol overhead per port (16ns per crossing)
hbm_ctrl.efficiency 0.8 HBM effective BW factor (256 to 204.8 GB/s)
xbar.overhead_ns 2.0 Crossbar arbitration delay
xbar_to_hbm_bw_gbs 256.0 Raw HBM bandwidth per slice

Project Structure

kernbench/
+-- src/kernbench/
|   +-- cli/            # CLI entry points (main, probe, report)
|   +-- common/         # Shared types (Completion, RequestHandle, Trace)
|   +-- components/     # Hardware component models (SimPy processes)
|   +-- di/             # Dependency injection
|   +-- policy/         # Routing (XY), address decoding (PhysAddr)
|   +-- runtime_api/    # Host-facing API (messages, bench runner)
|   +-- sim_engine/     # Discrete-event engine, transaction, wire model
|   +-- topology/       # YAML builder, mesh generator, graph types
|   +-- triton_emu/     # Triton kernel emulation
+-- benches/            # Benchmark implementations
+-- tests/              # pytest test suite (278 tests)
+-- docs/               # ADRs, latency model docs, diagrams
+-- topology.yaml       # System topology configuration
+-- CHANGES.md          # Changelog

Documentation

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