ywkang 95cecccd8e gqa(adr): ADR-0064/0065 review fixes — composite size cap, type-aware logical_bytes, R recalibration
ADR-0064 Revision 2 review fixes:
- D7 NEW: composite size cap (MAX_COMPOSITE_LOGICAL_BYTES default 1024
  bytes). Oversized recipes deterministically segmented into N
  CompositeCmds; each segment incurs its own dispatch cost. Models real
  HW limits (descriptor queue entry, scheduler parser buffer, command
  SRAM) and prevents the model from rewarding pathologically-large
  fused composites.
- D2: type-aware extra-field byte counting (int/float=4, bool=1,
  tuple/list=1+4N, str=1) — replaces uniform 4 bytes per extra.
- D3: recalibrated defaults to FIXED=40 cycles, R=0.0625 cycles/byte
  (16 B/cycle — typical on-die descriptor queue width); anchor stays at
  ~43 ns for typical 1-OpSpec composite. Clarified anchor description:
  DMA stages do not appear in logical_bytes (auto-inserted by
  PE_SCHEDULER from operand.space per ADR-0065 D4).
- D4: removed clock_freq_ghz from pe_cost_model: override block;
  conversion uses the PE node's existing clock_freq_ghz attr. Added
  max_composite_logical_bytes knob.
- Context: emphasized command-count reduction (FIXED) as the primary
  signal; byte term as secondary refinement.
- Open review: added large-composite scheduler-cost stress test.
- Test req: added composite-size-cap (#8) and R-sensitivity sweep (#9).

ADR-0065 + DDD-0065 follow-on updates:
- opt2 vs opt3 dispatch ratio updated 2.4× → ≈4.0× under new defaults
  (FIXED-dominated, reflecting the corrected framing).
- Test req #9: decode opt2 composite fits within 1024-byte cap; no
  segmentation needed for the GQA workload.
- DDD §6: TLContext lowering checks logical_bytes against cap (step 8).
- DDD §11: performance model recomputed with new defaults + sensitivity
  table across R ∈ {0.25, 0.0625, 0.03125} confirming opt2 < opt3 holds.
- DDD §9 P6 gate: ratio band 2.4×±10% → 4.0×±15%; sensitivity sweep added.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-10 16:21:58 -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

S
Description
No description provided
Readme 70 MiB
Languages
Python 97.6%
HTML 2.4%