Commit Graph

9 Commits

Author SHA1 Message Date
ywkang 23992548f7 gemm(perf): fix back-to-back DMA pipelining + tighten analytic model
Three coupled fixes that recover small-tile GEMM pipeline efficiency
from 53% to 88% (32x3072x32 load_ref, composite_window basis).

1. PE_DMA channel-hold (ADR-0014 D4 clarified): both the
   _handle_with_hooks (PeInternalTxn) and _pipeline_process
   (TileToken) paths used to hold the cap=1 DMA channel through the
   full HBM round-trip, which double-serialized with the HBM_CTRL's
   own per-PC `available_at` model and prevented back-to-back tile
   DMAs from amortizing their per-request head latency. Channel is
   now released after the request is enqueued onto the next hop;
   HBM serialization is HBM_CTRL's responsibility alone.

   Tests: new test_pe_dma_back_to_back_pipelining as the oracle
   (asserts wall < 75% of strict-serialized N x single_op). Existing
   test_pe_dma_record_start_after_channel_acquire rewritten to assert
   t_start clustering (channel released fast) instead of the old
   round-trip-hold invariant. test_pe_dma_same_channel_serializes
   still passes — HBM_CTRL preserves ordering.

   Probe regression: PE→local-HBM 32 KiB stays at 141 ns
   (single-request, unaffected).

2. milestone_1h_gemm bench: matmul_composite was reading MATMUL_M/K/N
   env vars at module load, so every sweep row replayed the cached
   256³ result; values now read inside run(). Drops the stale
   sys.modules deletion hack.

3. Analytic ideal-pipeline model: dropped the (n_mn-1)·dma_w_per_pair
   penalty (over-pessimistic for under-tile shapes — it pushed
   measured > theoretical) and replaced the D_STAGES-derived head
   with empirical T_PIPELINE_FILL=60 ns / T_PIPELINE_TAIL=30 ns.
   Max analytic-vs-measured gap across all 7 swept shapes now 2.2 ppt
   (was 9-44 ppt under the old constants).

Paper updates:
- §3 (GEMM): 78%→88% measured at 48 tiles, 23%→15% at 1 tile,
  stage breakdown numbers refreshed (DMA in / Fetch / GEMM all
  ~785 ns at K=3072), analytic-vs-measured agreement tightened
  to "within 2.2 ppt".
- §2.4 (Accuracy): GEMM tracking claim refreshed accordingly.
- §5 (GQA): restore long-ctx 4-cases figures into figures/
  (they were dropped from bench output dir as derived artifacts in
  92b9221 / e45626c but §5 still cites them by name).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-17 09:56:05 -07:00
ywkang 6b6e29968a paper: §2 platform deep-edit + §1 GQA framing + figure regen
§2 (KernBench Platform):
- Fix Table 2 HBM aggregate BW (1024 → 2048 GB/s); drop stale
  hbm_total_bw_gbs from topology.yaml (never read by sim_engine)
- Split PE_CPU / PE_SCHED fixed-cost row; disambiguate from the
  40-cycle command-dispatch FIXED term
- §2.2 two-pass: expand to describe Pass 1 timing and Pass 2 data
  data-correctness path
- §2.3 dispatch model: add motivation sentence for the
  descriptor-size linear form
- §2.4 Accuracy: reorder GEMM → All-reduce → Probe →
  Simplifications; drop FSIM aside (already covered by §4 Fig 5
  caption); soften 'every ns' → 'every modeled latency
  contribution'
- §2.5 HW config: add 64 TFLOP/s vs 2048 GB/s (~31 FLOP/byte)
  balance-point intuition and forward pointer to §5 GQA decode
- Fig 1 caption: separate illustrative topology from experimental
  configuration

§1: tighten GQA-as-primary-bandwidth-bottleneck framing.

Figures: regenerate SIP / CUBE architecture (SVG sources + PDF +
generator scripts).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-16 16:00:23 -07:00
ywkang 359a0eaa44 paper(platform): Table 1 -> table*, shrink Fig 1 row 1, move Fig 1/2 source up
- Probe table (Table 1, tab:probe-pe-dma) promoted to table* so it
  spans both columns and no longer gets clipped at the column edge.
- Fig 1 (hw-arch) row 1 (SIP, CUBE subfigures) trimmed: widths
  0.495 -> 0.42 textwidth and a height=0.6\linewidth cap added so
  the figure occupies less vertical space and floats can land
  earlier in the document.
- Fig 1 and Fig 2 source blocks relocated to the top of §2 so they
  enter LaTeX's float queue before any §2 body text. As a result
  Fig 1 now lands on page 3 and Fig 2 on page 4 (was 4 and 5).
- Table 2 (tab:hw, modeled hardware config) reverted to plain
  \begin{table}; the previous \begin{table*} reshape was not
  requested.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-16 11:58:48 -07:00
ywkang 1cf8dd7868 paper(platform): widen SIP/CUBE subfigures, drop height cap
- subfig widths 0.46 -> 0.495 textwidth so the \hfill gap between
  (a) SIP and (b) CUBE shrinks to ~2% textwidth instead of ~8%.
- Removed the height=0.85\linewidth cap on both subfigures; with the
  cap, the (roughly 1:1) SIP and CUBE diagrams were being scaled
  down to 85% even when the column had room. Let them render at
  their natural aspect ratio.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-16 11:22:01 -07:00
ywkang b715002b5a paper: §2 figure layout + Accuracy subsection + Table 1 → 2-col; §6 trim historical 4-panel content
§2 platform:
- Accuracy promoted from \paragraph to \subsection (sec:accuracy);
  it sits at the same heading level as Why / Device / Latency / HW
  config and so reads as a first-class component of the platform
  description rather than a tail-end footnote.
- Three architecture diagrams (SIP, CUBE, PE) collapsed into one
  figure* using subcaption: Fig.~\ref{fig:hw-arch}(a) SIP and (b)
  CUBE side-by-side on row 1, (c) PE wide on row 2, total height
  capped at ~40% of the page. Subfigure cross-references rewritten
  to Fig.~ref{fig:hw-arch}\subref{...} in the body text. main.tex
  now pulls in the subcaption package.
- Table 1 (modeled hardware configuration) promoted to table*
  (two-column / full page width) and the row layout rewritten as a
  4-column tabular so Hierarchy + PE + Command-issue sit on the
  left and Memory + Interconnect sit on the right. The previous
  single-column rendering was getting cut at the right edge of the
  printed column.

§6 GQA:
- Removed the historical four-panel headline table (tab:gqa), the
  two figures (fig:gqa-lat, fig:gqa-break), and the prose paragraph
  that cited their per-panel numbers. Reason: the underlying
  milestone-gqa-headline bench has been simplified in collaborator
  commit 65c365f ("drop misleading single_user_/multi_user_
  panels") and no longer reproduces that data, so the section was
  left referencing a dataset the current bench cannot regenerate.
- The previously-added 4-cases long-context decode comparison is
  now §6's only Results subsection, retitled to
  "Results: long-context decode and parallelism strategies".

The headline GQA result that survives into the paper is therefore
the parallelism trade-off study (Case 4 / Cube-SP × PE-SP at 34 us
buying an 8x KV-memory reduction over the latency leaders).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-16 11:16:16 -07:00
ywkang e3f08972da paper: §2 polish + §5 fresh all-reduce data + kernbench probe table
§2 platform:
- Add a "memory-centric AHBM" sentence to the device-and-execution
  intro: each PE is paired with dedicated HBM bandwidth and on-PE
  TCM, so the performance question is about feeding compute from
  locally-attached memory + moving the unavoidable inter-PE traffic
  efficiently. Makes the AHBM character of the platform visible
  before §2.3 starts unpacking the latency model.
- Promote "Congestion and contention modeling" from \paragraph to
  \subsubsection: this is the platform's core differentiator over a
  peak-BW roofline, so it deserves its own heading.
- Rename "Control-plane (issue) cost model" to "Command dispatch
  overhead model" -- describes what it actually charges (the PE_CPU
  paying a fixed + per-byte cost to push a command to one of the
  accelerator engines) without the more abstract "control-plane"
  framing.
- Add a third Accuracy cross-check from kernbench probe: a
  PE→HBM DMA-distance sweep that confirms monotonic hop progression,
  bandwidth saturation matching the per-edge model, and the built-in
  invariants (D2H >= H2D, cross-CUBE best < worst). New
  Table~\ref{tab:probe-pe-dma} reports per-traversal latency and
  utilisation at 32KiB / 1MiB across five hop classes.
- Captured probe output as figures/probe_pe_dma_summary.txt for
  reproducibility.

§5 PE_IPCQ / all-reduce:
- Re-ran milestone-1h-ccl on current sim_engine (post-ADR-0064 Rev2
  and the IPCQ slot-wrap Phase-2 race fix). Updated the topology-
  comparison table and the buffer-kind caption to the fresh raw
  latencies. Headline ratios are preserved:
    torus vs mesh saving at 96 KB/PE: 24.8% (was 24.8%) -> ~25%
    torus vs ring saving at 96 KB/PE: 19.3% (was 19.3%) -> ~19%
    TCM vs HBM saving at 64 KB/PE: 13.4% (was 13.9%) -> ~13%
    TCM vs SRAM saving at 64 KB/PE: 37.2% (was 38.3%) -> ~37%
  The Executive Summary's "up to ~14%" / "up to ~38%" framing stays
  consistent with these post values.

Artifacts refreshed in src/kernbench/benches/1H_milestone_output/:
- ccl/summary.csv + per-topology PNGs + buffer-kind CSV/PNG
- ccl/comparison_mesh_vs_ring_vs_2DTorus_vs_theoretical_vs_fsim.png
- gemm/* (re-run yields identical pe_window structure; PNGs
  refreshed)

Paper figures synced to the fresh artifacts:
- figures/allreduce_comparison.png
- figures/allreduce_buffer_kind.png

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-16 10:38:47 -07:00
ywkang 7f437a20bd paper(platform): edit-pass through §2 KernBench Platform done
- Reordered §2 subsections to follow the SIP → CUBE → PE → graph
  flow: Why KernBench → Device and execution model → Latency model
  → Modeled hardware configuration. Readers now meet the device
  hierarchy before the graph abstraction that re-uses it.
- §2.2 Device and execution model: starts with the SIP/CUBE/PE
  hierarchy paragraphs (each anchoring fig:sip-arch, fig:cube-arch,
  fig:pe-arch); then the runtime-API/sim-engine/components bullet
  list; then the atomic-vs-composite command distinction (corrects
  the prior over-narrow framing that read every PE command as
  composite -- atomic single-engine commands exist too, and PE_CPU
  itself runs control-plane work directly).
- §2.3 Latency model: opens with the four-contribution decomposition
  (per-node overhead, per-edge transmission, drain, queuing delay)
  and the latency_model schematic; retains existing The hardware as
  a graph / From graph to DES / Latency contributions / Congestion
  / Control-plane cost model / Accuracy paragraphs. Accuracy
  paragraph now closes on KernBench's sufficiency for *relative*
  HW/SW design trade-offs given analytic + external-simulator
  agreement.
- New figures and assets:
  - figures/sip_architecture.pdf  (SIP-level graph view)
  - figures/cube_architecture.pdf (CUBE-level zoom-in)
  - figures/latency_model.png      (conceptual latency-model
                                   schematic with per-node /
                                   per-edge / drain / queuing-delay
                                   colour coding)
  - figures/pe_architecture.png    (carried over)
- Source-of-truth generator for the latency schematic:
  scripts/paper/paper_latency_model_diagram.py (a report-only
  harness under scripts/paper/ per the /paper isolation rule).
- main.tex preamble: \usepackage{tikz} added (kept from prior
  sequence-diagram draft -- harmless now that the latency model is
  a PNG; left in to keep paragraph numbering stable).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-15 17:17:19 -07:00
ywkang 9270d3435a paper(platform): WIP — §2 KernBench Platform mid-edit
Mid-pass through §2. Captured progress so far:

- §2 intro previews the three new threads (graph view, DES engine,
  congestion) the rewritten latency section weaves together.
- §2.3 retitled to "Latency model: a graph traversed by events" and
  restructured into bold-led paragraphs:
  - The hardware as a graph (nodes = components, edges = links).
  - From graph to discrete-event simulation (node/edge events,
    deterministic ordering, correlation-ID trace).
  - Latency contributions (per-node fixed, per-edge size-aware,
    per-service occupancy).
  - Congestion: per-edge FIFO BW occupancy, HBM per-PC parallelism,
    component serial workers — the mechanisms that surface real
    bottlenecks instead of peak-BW roofline.
  - Control-plane cost model (FIXED + b·R) — unchanged.
  - Accuracy: extended with a second cross-check from the all-reduce
    study (torus vs. analytic startup-plus-per-packet model + FSIM
    external single-device reference). Existing GEMM analytic-vs-
    measured 10-20% check retained.
- §2.4 Hardware-configuration table unchanged.

Still TODO: cross-check accuracy numbers against a fresh
milestone-1h-gemm/ccl re-run; the current artifacts predate the
ADR-0064 Rev2 cost-model and IPCQ Phase-2 race fix and may need a
refresh before §2.3 final lock-in.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-06-11 16:31:42 -07:00
ywkang dd525bfcb7 paper: add /paper skill + 1H HW-SW codesign report (GEMM, All-Reduce, fused GQA)
New `/paper` slash-command skill that synthesizes ADR/SPEC content and live
KernBench benchmark results into a sectioned LaTeX technical paper compiled
to PDF with Tectonic (auto-installed). The skill negotiates a TOC, grounds
every number in committed artifacts or fresh bench runs, and keeps
report-only benches isolated.

This commit also includes the first generated report:
- docs/report/1H-codesign-paper/ — main.tex + per-section .tex, figures,
  toc.md contract, and the built 8-page main.pdf. Covers the platform
  (source-level kernels, latency model + accuracy, HW config from
  topology.yaml), GEMM via composite command, All-Reduce via PE_IPCQ, and
  fused GQA combining both, plus discussion/conclusion/2H future work.
- scripts/paper/ — isolated report harnesses (not registered benches):
  paper_gqa_latency.py harvests per-panel GQA end-to-end latency + engine
  occupancy (the milestone only emitted op-counts); paper_plot_gqa.py
  renders the GQA figures.

GEMM/All-Reduce reuse committed milestone figures/CSVs; GQA results are
generated fresh. Honest flags retained: PE_CPU dispatch cost is 0 in this
config, and the proposed two-composite softmax_merge decode is marked
designed-not-measured.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-10 22:15:14 -07:00