ywkang a8d04750e6 gqa(adr): ADR-0065 review fixes — KERNEL phase/repetition split, auto-bind conflict + MATH-TCM invariants, FIFO conservatism note, logical_bytes per-op summation
ADR-0065 review fixes:
- D3 semantics clarified: position determines *phase* (pre-loop / head /
  in-accumulation / per-output-tile / post-loop), scope determines
  *repetition*. KERNEL = "once per CompositeCmd invocation", not "once
  per kernel launch" — removes ambiguity around softmax_merge's KERNEL
  scope at different positions before/after GEMM.
- D4 MATH-TCM invariant: Phase 1 limits DMA auto-insertion to GEMM
  operands and head outputs; MATH operand with space="hbm" raises
  validation error at TLContext emit. Catches kernel misuse early; a
  MATH-with-HBM path is future work (explicit tl.load + MATH composite).
- D6 #6 NEW: auto-bind conflict — explicit GEMM `a=` + prologue
  primary_out simultaneously → validation error (prevents "which value
  wins" ambiguity).
- D6 #7 NEW: MATH operand TCM-only restatement.
- Consequences/Negative: strict-FIFO conservatism note — safe but may
  under-expose composite-level overlap when handle-sharing composites
  could in principle run in parallel.
- Test Requirements #10, #11: auto-bind conflict + MATH-HBM validation
  error tests.

ADR-0064 Revision 2 clarification:
- D2 counting rule: per-op summation, no deduplication. Same handle
  appearing in multiple OpSpecs or in rw_handles is counted
  independently — matches HW reality (each descriptor field is a
  distinct address slot, rw_handles is separate metadata block).
  Example walked through (mul_bcast with O in src_a + out + rw_handles).

DDD-0065 follow-on:
- §3.2: new test file test_tl_composite_validation.py covers auto-bind
  conflict, MATH-TCM, GEMM-count invariants.
- §4.3: phase vs repetition split aligned with ADR-0065 D3.
- §6 lowering pipeline: step 5 adds auto-bind conflict check; step 8
  NEW — operand space validation; step 9 (size cap); step 10 (emit).
- §8 strict-FIFO conservatism note: explains why next-tile #1 cross-tile
  pipelining still works under FIFO (no rw overlap), and where the
  conservatism would hurt (future handle-sharing recipes).
- §10 verification: invariant-guard tests (auto-bind conflict, MATH
  TCM, per-op summation accuracy).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-10 16:29:39 -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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