55f025c4b1
tiling.generate_plan_from_ops: scan flat ops for the GEMM (<=1); pre-GEMM KERNEL ops become single-shot prologue MATH stages, post-GEMM ops split by scope (K_TILE/OUTPUT_TILE epilogue + KERNEL post-loop). MATH-only composite reproduces the legacy math-head plan. Prologue/post-loop stages fold into the first/last tile so the feeder + completion counting are untouched (existing benches have neither -> byte-equal op_log). PipelinePlan gains prologue_stages/epilogue_stages. pe_scheduler._generate_plan delegates to generate_plan_from_ops. DMA keeps the existing pinned signal (NOT a space flip); recipe scratch/primary-out handles are pinned=True so the head GEMM's auto-bound a (=P) is consumed in place. ADR-0065 D4/D6.7/Test#5 amended (EN+KO): DMA decision from pinned, not space; prologue recipe ops TCM-only (head op exempt -- it may stream from HBM). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
449 lines
22 KiB
Markdown
449 lines
22 KiB
Markdown
# ADR-0065: Flat-ops `CompositeCmd` + first stateful recipe (`softmax_merge`)
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## Status
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Proposed (verification gated on ADR-0064 Revision 2 land)
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> Supporting ADR for **ADR-0060** (AHBM GQA Fused Attention). Implements
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> the §5.6 / §8 item 4 carve-out exactly: opt2 of decode = (#1 existing
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> GEMM composite for Q·Kᵀ) + (#2 a single composite carrying softmax +
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> P·V + online-softmax merge). The "ex_composite" / "flash_pv_merge" name
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> referenced in ADR-0060 §5.6 is *retired* — this ADR fixes the canonical
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> shape using the existing `tl.composite` entry with two structural
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> additions: (a) a flat `ops` tuple, and (b) a first stateful recipe
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> `softmax_merge` that lowers to a sequence of MATH micro-ops.
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## Context
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### What ADR-0060 left to this ADR
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ADR-0060 §5.6 shipped opt3 (software pipelining) as the recommended now,
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and explicitly carved out opt2 — fewer per-tile dispatches, K-before-V
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DMA priority, **measurable only after ADR-0064**'s cost model — as the
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follow-up.
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§8 item 4 sized the carve-out: "if revisited, split it into **two**
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composites — `#1` = Q·Kᵀ (existing composite + `scale`), `#2` = softmax +
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P·V + online-softmax accumulator merge". This ADR implements `#2`.
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### Why composite needs a structural change
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Today's `CompositeCmd` has the shape `(op, a, b, out_addr, ops=(head,
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*epi))` with implicit conventions:
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- `op` selects the head engine (gemm | math)
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- `ops[0]` is the head OpSpec, `ops[1:]` are epilogue OpSpecs that run
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*after* the head per-output-tile or per-K-tile (scope-determined)
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For decode opt2 we need MATH ops to run **before** the head GEMM (the
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online-softmax `m, l, O` update + emit `P` for the GEMM input). The
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current shape has no slot for that.
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Two failed paths considered earlier:
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- Embedding softmax_merge as an *epilogue* of #1 (Q·Kᵀ) — wrong: it
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needs to read `Sj` (= #1's output) and writes a fresh `P` consumed by
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the *next* GEMM (#2's P·V); circular.
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- A single mixed-engine recipe `flash_pv_merge` absorbing MATH + GEMM +
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MATH — violates the engine boundary, complicates PE_SCHEDULER.
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The clean shape is: **drop the head/epilogue distinction from the
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command format**. Make `ops` a flat ordered tuple; let each op's
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`scope` + position determine its tile-loop placement. The "prologue"
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concept stays in the *user-facing* `tl.composite(...)` API as
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ergonomics — but the **HW command never sees it**.
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### Why a recipe (not a generic op list)
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Decode opt2's `#2` MATH chain is 8 steps with a fixed structure (online
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softmax merge). Letting the kernel author wire those 8 steps would be
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both verbose and a hazard surface (correctness depends on step order).
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A *recipe* — a single named op (`softmax_merge`) that TLContext expands
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to the 8 steps with addresses pre-filled — keeps the kernel concise and
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the structure under one source of truth. The recipe table lives in
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TLContext (the compiler analog); PE_SCHEDULER never reads it. See
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boundary in D5.
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## Decision
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### D1. `CompositeCmd` is a flat ordered op list
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```python
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@dataclass(frozen=True)
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class CompositeCmd:
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completion: CompletionHandle
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ops: tuple[OpSpec, ...] # ordered MATH/GEMM ops
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rw_handles: tuple[TensorHandle, ...] = () # cross-composite hazard
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data_op: bool = True
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@property
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def logical_bytes(self) -> int: ... # ADR-0064 D2
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```
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The previous `(op, a, b, out_addr, out_nbytes, math_op)` fields are
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absorbed into `ops`. The first OpSpec in `ops` (if `kind == "gemm"`) is
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the head GEMM; preceding OpSpecs are pre-loop ops, following OpSpecs
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are post-loop / per-tile epilogue ops depending on `scope`.
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### D2. `OpSpec` carries named operands
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```python
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@dataclass(frozen=True)
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class OpSpec:
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kind: str # "gemm" | "rmax" | ...
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scope: Scope # KERNEL | K_TILE | OUTPUT_TILE
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operands: dict[str, TensorHandle] # named — see D5
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extra: dict[str, Any] # scalars, axes, m/k/n, etc.
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out: TensorHandle | None = None # explicit write-back handle
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@property
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def logical_bytes(self) -> int: ...
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```
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Named operands let PE_SCHEDULER route inputs to engine ports (e.g., GEMM
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takes `operands["a"]`, `operands["b"]`) without positional convention.
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### D3. Position + scope determines tile-loop placement
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**Semantics split.** *Position* determines the **phase** (where in the
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tile-loop lifecycle the op fires); *scope* determines the **repetition**
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within that phase. `Scope.KERNEL` means "**once per `CompositeCmd`
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invocation**", not "once per kernel launch" — its single firing happens
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at the op's position in the sequence. The same KERNEL value carries
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different *phases* depending on whether the OpSpec sits before, at, or
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after the GEMM op.
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PE_SCHEDULER scans `cmd.ops` for the GEMM op (≤1 per CompositeCmd, see
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D6). Calling its index `g`:
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| OpSpec position | scope | Phase | Placement in plan |
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|---|---|---|---|
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| `0 .. g-1` | KERNEL | pre-tile-loop | run once before tile loop |
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| `g` | KERNEL | head GEMM | drives tile loop with `extra["m"], extra["k"], extra["n"]` |
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| `g+1 .. ` | K_TILE | in-accumulation | per K-tile epilogue (inside K accumulation loop) |
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| `g+1 .. ` | OUTPUT_TILE | per-output-tile | per (m, n) tile epilogue (after K accumulation) |
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| `g+1 .. ` | KERNEL | post-tile-loop | run once after tile loop |
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A composite with no GEMM op (e.g., MATH-only composite) treats all ops
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as KERNEL-scope sequential — phase collapses to "single-shot in order".
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### D4. PE_SCHEDULER auto-inserts DMAs from the operand `pinned` flag
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PE_SCHEDULER scans the GEMM's `operands`. For each:
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- **not `pinned`** (data lives in HBM, must be streamed) → emit DMA_READ
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Stage before the FETCH/GEMM Stages
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- **`pinned`** (already staged in TCM via a prior `tl.load`, or a recipe's
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TCM scratch / primary-out `P`) → no DMA Stage, consumed in place
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The kernel never emits explicit DMA cmds for composite operands;
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PE_SCHEDULER infers them from handles. `tl.ref` operands are not pinned
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(DMA_READ); `tl.load` results and recipe scratch / primary-out are pinned
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(in place).
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> **As-built note (P3).** An earlier draft of D4 derived the DMA decision
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> from a `space` tag (`hbm`→DMA, `tcm`→in place) and would have flipped the
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> current `space` values (today `tl.load`=`hbm`, `tl.ref`=`tcm`). The
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> implementation **keeps the existing `pinned` flag** as the DMA signal
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> instead — `pinned` already encodes "already in TCM, skip DMA", flipping
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> `space` would change existing bench Stage sequences for no functional
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> gain. Unifying `space` and retiring `pinned` is a deferred low-priority
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> cleanup.
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**Prologue recipe ops are TCM-only (Phase 1 limit, enforced at TLContext
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emit).** Every operand of a *prologue recipe* (non-GEMM) OpSpec **must** be
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TCM-resident; passing an HBM handle as a recipe operand raises a validation
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error at emit time. This bounds DMA staging to the head op's operands in
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Phase 1. The **head op itself** (gemm *or* math) keeps the existing
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DMA-staged-from-HBM behavior — D4's TCM-only rule does **not** apply to it.
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This invariant is also restated in D6 #7.
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### D5. RECIPE_DESCRIPTORS — TLContext-internal, NOT in `pe_commands.py`
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Recipes live in a new TLContext-adjacent module
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(`src/kernbench/triton_emu/tl_recipes.py`). PE_SCHEDULER does **not**
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import it. The first recipe:
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```python
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@dataclass(frozen=True)
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class RecipeDescriptor:
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# Operand contract: name → "R" (read-only) | "RW" (read-write)
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operands: dict[str, str]
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# Type / shape rule for the implicit primary output (auto-bound to
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# head's first matrix operand). None means recipe emits no value.
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primary_out: PrimaryOutSpec | None
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# Single-shot prologue (full reduction) vs tile-aligned execution.
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tile_alignment: Literal["single_shot", "tile_aligned"]
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# Internal scratch budget (bytes), function of operand dims.
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internal_scratch_bytes_fn: Callable[..., int]
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# Engine micro-op sequence: TLContext expands this into flat OpSpecs.
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engine_seq: tuple[EngineOp, ...]
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RECIPE_DESCRIPTORS["softmax_merge"] = RecipeDescriptor(
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operands={"s": "R", "m": "RW", "l": "RW", "O": "RW"},
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primary_out=PrimaryOutSpec(
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from_shape="s", from_dtype="s", transform="identity",
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),
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tile_alignment="single_shot",
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internal_scratch_bytes_fn=lambda G, TILE, d, bpe: bpe * (
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G + G + G + G * TILE + G # m_loc + m_new + corr + P + l_loc
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),
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engine_seq=(
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EngineOp("MATH", "rmax", src="s", dst="m_loc", reduce_axis=-1),
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EngineOp("MATH", "max_elem", src_a="m", src_b="m_loc", dst="m_new"),
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EngineOp("MATH", "exp_diff", src_a="m", src_b="m_new", dst="corr"),
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EngineOp("MATH", "exp_diff", src_a="s", src_b="m_new", dst="P", bcast_axis=0),
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EngineOp("MATH", "rsum", src="P", dst="l_loc", reduce_axis=-1),
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EngineOp("MATH", "fma", src_a="l", src_b="corr", src_c="l_loc", dst="l"),
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EngineOp("MATH", "mul_bcast", src_a="O", src_b="corr", dst="O", bcast_axis=1),
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EngineOp("MATH", "copy", src="m_new", dst="m"),
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),
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)
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```
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TLContext, on `tl.composite(prologue=[{"op": "softmax_merge", ...}],
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op="gemm", ...)`:
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1. Validates operand R/RW against `RECIPE_DESCRIPTORS["softmax_merge"]`.
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2. Allocates scratch (m_loc, m_new, corr, P, l_loc) via the scratch_scope
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helper (ADR-0063).
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3. Derives the primary output P's shape from `s.shape` (identity).
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4. Expands `engine_seq` into 8 flat MATH OpSpecs with all addresses /
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sizes filled. Each OpSpec gets `scope=KERNEL`.
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5. **Auto-binds (with conflict check, D6.6).** If the head GEMM does
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*not* explicitly provide `operands["a"]`, auto-bind
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`operands["a"] = P_handle`. If the kernel *did* provide `a`
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explicitly, emit a validation error — ambiguous primary-output
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replacement.
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6. Emits `CompositeCmd(ops=(8 MATH + 1 GEMM + epilogue), rw_handles=
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(m, l, O))`.
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**RECIPE_DESCRIPTORS appears nowhere in the HW path**. PE_SCHEDULER
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sees only the flat ops list.
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### D6. Invariants
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1. **GEMM count.** `0 ≤ count(op.kind == "gemm" in cmd.ops) ≤ 1`. A
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composite with 0 GEMMs is MATH-only.
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2. **softmax_merge has no V operand.** `RECIPE_DESCRIPTORS["softmax_merge"
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].operands` does not include any HBM-resident handle → no DMA inserted
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during the prologue → V DMA can only happen during the GEMM head →
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natural K-before-V DMA priority across #1 / #2 of decode opt2.
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3. **Strict FIFO across composites.** PE_SCHEDULER tracks in-flight
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`rw_handles`. A new composite whose `rw_handles` (or any of its op
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inputs) intersect with an in-flight composite's `rw_handles` waits
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for all earlier composites to complete — no out-of-order reorder.
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4. **No backwards-incompatibility for legacy callers.** The user-facing
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API `tl.composite(op="gemm", a, b, epilogue=[...])` is preserved.
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TLContext internally lowers it to a flat-ops `CompositeCmd`.
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5. **PE_SCHEDULER recipe-free.** PE_SCHEDULER does not import
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RECIPE_DESCRIPTORS, does not know that "softmax_merge" exists, and
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has no recipe-specific code branches.
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6. **No implicit operand replacement (auto-bind conflict).** If a
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prologue recipe declares a `primary_out` AND the head op's auto-bind
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target operand (e.g., GEMM `a`) is *also* provided by the kernel
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explicitly, TLContext raises a validation error at emit time. The
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kernel must either let the recipe bind (omit the operand) **or**
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specify it explicitly (omit the prologue, or use a recipe without
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`primary_out`). This prevents the ambiguity of "which value wins".
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7. **Prologue MATH operands TCM-only.** Restatement of D4: every operand
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of a *prologue recipe* (non-GEMM) OpSpec must be TCM-resident. The head
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op (gemm or math) is exempt — it may stream from HBM. Phase 1 enforced
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at TLContext emit.
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### D7. Boundary summary (compiler vs scheduler vs engine)
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```
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HOST DEVICE
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TLContext (compiler analog) PE_SCHEDULER (scheduler/dispatcher)
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- validate against RECIPE_DESC. - scan flat ops list
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- derive primary_out shape - identify GEMM (≤1)
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- allocate scratch - position-based stage placement
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- expand recipe → flat OpSpecs - auto-insert DMA stages from space
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- compute rw_handles - strict-FIFO RW hazard tracking
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- emit CompositeCmd - emit Stage list
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imports: RECIPE_DESCRIPTORS imports: nothing recipe-related
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ENGINES (PE_MATH / PE_GEMM / PE_DMA)
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- read Stage.params (op_kind, addresses, n_elements)
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- existing latency models unchanged
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imports: nothing recipe-related
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```
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## Alternatives
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### A1. Three composites per tile (no prologue concept)
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Split #2 further into `softmax_merge` + `gemm(P·V)` + `add(O)` as three
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separate CompositeCmds. Pros: no flat-ops restructuring (`add` reuses
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existing epilogue path). Cons: 3 dispatches per tile instead of 2 —
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diverges from ADR-0060 §8 item 4 sizing ("split into **two**"); loses
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~32 ns × N_tiles of fixed-cost savings. **Rejected.**
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### A2. Mixed-engine recipe (`flash_pv_merge`)
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One recipe absorbing MATH + GEMM + MATH (ADR-0060 §5.6 original
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phrasing). Pros: tightest dispatch (1 composite). Cons: PE_SCHEDULER
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must know engine-boundary recipes, violates the "engines see only
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Stage.op_kind" boundary, recipe table becomes ISA-like and pollutes
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HW interface. **Rejected.**
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### A3. Generic op-list DAG (`tl.ex_composite([...])`)
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User-defined sequence of any ops with named slots and dataflow analysis.
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Pros: maximally flexible. Cons: a single user (softmax_merge) does not
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justify a generic DAG language; PE_SCHEDULER would need dataflow
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analysis; reintroduces ADR-0060 §8 item 4's "absorb the inner loop"
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trap. **Rejected (Simplicity First).**
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### A4. RW-aware scheduler reorder (not strict FIFO)
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PE_SCHEDULER could allow a later CompositeCmd to overtake an in-flight
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one when their `rw_handles` don't intersect (e.g., next-tile #1 could
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overlap with this-tile #2 since #1 doesn't touch m/l/O). Pros: more
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overlap. Cons: more scheduler state, gains are bounded (next #1 waits
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for K DMA anyway). **Deferred** — strict FIFO ships first; RW-aware
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reorder may be a future follow-up ADR.
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### A5. Embedding softmax_merge as an epilogue of #1 (Q·Kᵀ)
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Wrong: softmax_merge's output `P` is the input of #2's P·V GEMM, which
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runs *after* #1's epilogue. Embedding it would force #2 to read its own
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input from #1's epilogue scratch — circular tile-loop dependency.
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**Rejected (incorrect).**
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## Consequences
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### Positive
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- ADR-0060 §5.6 / §8 item 4 carve-out implemented exactly: opt2 = 2
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composites per tile, K-before-V DMA priority natural.
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- Composite contract becomes uniform: flat ops list with scope-based
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placement. No structural distinction between "head" and "epilogue"
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in the HW cmd.
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- DMAs auto-inferred from operand `space`; kernel surface simpler.
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- HW interface (`CompositeCmd` shape) stays small even as recipes grow
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— recipe expansion happens host-side.
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- New fused patterns (linear+gelu+norm, rmsnorm+linear, …) can be added
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by inserting one `RECIPE_DESCRIPTORS` entry; no PE_SCHEDULER changes.
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### Negative
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- CompositeCmd's struct shape changes — a refactor for all current
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callers. Semantics preserved (D6.4); existing goldens unchanged once
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ADR-0064 Revision 2 lands.
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- `OpSpec.operands` changes from positional `tuple[Any, ...]` to
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`dict[str, TensorHandle]` — touches the existing epilogue lowering.
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- New TLContext code: recipe expansion + scratch-slot allocation +
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primary_out auto-bind. ~80–120 LOC.
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- PE_SCHEDULER's `_generate_plan` gets a position-based scan + DMA
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auto-insertion + strict-FIFO RW tracker. ~60–100 LOC.
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- **Strict-FIFO RW hazard tracking is safe but conservative.** When
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two composites share any `rw_handle`, the new one waits for *all*
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prior overlapping composites to fully complete — even when their
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compute could in principle overlap (e.g., next-tile #1 = Q·Kᵀ does
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not touch m/l/O and could overlap with this-tile's #2, but FIFO
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still serializes any path that touches the same handles down the
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line). This **may under-expose composite-level overlap** relative to
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a smarter scheduler. RW-aware reorder (A4) is the deferred
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improvement.
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## Open review items
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1. **Recipe shape derivation rule beyond identity.** Future recipes may
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need non-identity transforms (e.g., transposed primary_out). The
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`PrimaryOutSpec.transform` field is forward-compat; add new
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transforms as needed.
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2. **Recipe scratch allocator** integration with ADR-0063's
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`scratch_scope`. Initial wiring: TLContext allocates inside the
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current `scratch_scope` context if active, else in a kernel-scope
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persistent slot.
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3. **`tl_recipes.py` location.** New module under `triton_emu/`. Keeps
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recipe knowledge co-located with the compiler analog (TLContext).
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4. **GEMM `out=TensorHandle`.** New form alongside legacy `out_ptr:
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int`. Both accepted; handle form preferred for new code (enables
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strict-FIFO RW tracking by handle identity).
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## Test Requirements
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1. **CompositeCmd flat-ops refactor — meaning preservation.** Every
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existing bench's op_log is byte-equal pre/post refactor (legacy API
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`tl.composite(op="gemm", a, b, epilogue=[...])` lowers to the same
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Stage sequence).
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2. **softmax_merge recipe lowering.** TLContext call `tl.composite(
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prologue=[{"op": "softmax_merge", "s": Sj, "m": m, "l": l, "O": O}],
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op="gemm", b=V_ref, out=O, epilogue=[{"op": "add", "other": O}])`
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produces a `CompositeCmd` with exactly 10 ops in the expected order
|
||
(8 MATH + 1 GEMM + 1 MATH(add)) and `rw_handles == (m, l, O)`.
|
||
3. **K-before-V DMA priority invariant.** op_log of decode opt2 shows
|
||
no V-related DMA during #2's MATH prologue (#2's V DMA begins only
|
||
when the GEMM head starts).
|
||
4. **Strict-FIFO RW serialization.** Two consecutive composites sharing
|
||
any `rw_handle` complete in dispatch order; their stages do not
|
||
interleave.
|
||
5. **DMA auto-insertion from `pinned`.** A GEMM composite with a
|
||
not-`pinned` operand (e.g. `b=tl.ref(...)`) emits a DMA_READ Stage; a
|
||
`pinned` operand (e.g. a recipe's TCM scratch / primary-out, or a
|
||
`tl.load` result) does not. (As-built D4 note: the DMA decision uses
|
||
the existing `pinned` flag, not a `space` tag.)
|
||
6. **opt2 numeric parity with opt3.** In data mode, opt2's final
|
||
`(m, l, O)` matches opt3's within fp tolerance.
|
||
7. **opt2 dispatch ratio (after ADR-0064 Rev2) — robust.** opt3 vs
|
||
opt2 per-tile PE_CPU dispatch cycles satisfies `opt3 > 2 × opt2`
|
||
(qualitative gate; calibration-independent). The default-calibration
|
||
model expectation is ≈ 4.0× (FIXED=40 cycles, R=0.0625 cycles/byte)
|
||
— see DDD-0065 §11 for the model-derived numbers; only the loose
|
||
`> 2×` bound is the test gate so it survives calibration changes.
|
||
Ratio is FIXED-dominated, reflecting command-count reduction as the
|
||
primary signal.
|
||
8. **GEMM-count invariant.** A composite with two GEMM OpSpecs raises a
|
||
validation error at TLContext emit.
|
||
9. **Within composite size cap (ADR-0064 D7).** Decode opt2's `#2`
|
||
composite (10 ops, ~322 logical bytes — per-op summation of operand
|
||
handles) fits comfortably under the default
|
||
`MAX_COMPOSITE_LOGICAL_BYTES=1024` — no segmentation. The recipe
|
||
lowering test asserts `cmd.logical_bytes < 1024`.
|
||
10. **Auto-bind conflict.** `tl.composite(op="gemm", a=A_handle,
|
||
prologue=[{"op": "softmax_merge", ...}], ...)` where softmax_merge
|
||
declares `primary_out` raises a validation error at emit time
|
||
(D6.6).
|
||
11. **MATH operand TCM invariant.** `tl.composite(op="math",
|
||
a=tl.ref(addr, shape), ...)` (passing an HBM-resident handle as a
|
||
MATH operand) raises a validation error at emit time (D6.7).
|
||
|
||
## Dependencies
|
||
|
||
- **ADR-0060** §5.6, §8 item 4 — the carve-out this ADR implements.
|
||
- **ADR-0064 Revision 2** — dispatch cost model; lands first, makes
|
||
opt2's fewer-issues win measurable.
|
||
- **ADR-0063** `scratch_scope` — recipe intermediates allocated inside;
|
||
`m, l, O` allocated outside as persistent arena (per DDD-0060 §6.2).
|
||
- **ADR-0046** `tl_context` contract — extended by `prologue=[...]`
|
||
kwarg, `out=TensorHandle`, RECIPE_DESCRIPTORS lookup.
|
||
- **ADR-0042** tile plan generators — extended (not redesigned) to
|
||
process the flat ops list and auto-insert DMAs.
|
||
- **ADR-0014** PE pipeline — boundary preserved: scheduler stays
|
||
recipe-free, engines stay op_kind-opaque.
|
||
|
||
## Migration
|
||
|
||
> **Implementation ordering note.** The ADR-0064-first ordering below was
|
||
> the original plan. The actual implementation **reversed steps 1 and 2** —
|
||
> ADR-0065 Phase 1 (flat-ops `CompositeCmd`) landed *before* ADR-0064 Rev2.
|
||
> Reason: `logical_bytes` (ADR-0064 D2) is naturally defined on the flat-ops
|
||
> shape, so doing the refactor first avoids a throwaway transitional
|
||
> `logical_bytes`. Each step is independently safe: P1 is a meaning-
|
||
> preserving refactor (op_log byte-equal) under the pre-existing cost path;
|
||
> ADR-0064 Rev2 then swaps in the structural formula on the already-flat
|
||
> shape. The end state is identical either way.
|
||
|
||
Land order (original plan; see note above for the as-built reversal of 1↔2):
|
||
1. **ADR-0064 Revision 2** (separate PR): structural dispatch cost +
|
||
`logical_bytes` property + topology config override + one-time
|
||
goldens regeneration.
|
||
2. **ADR-0065 Phase 1** (this ADR, PR a): `CompositeCmd` flat-ops
|
||
restructure + legacy-API lowering. Refactor only; goldens unchanged.
|
||
3. **ADR-0065 Phase 2** (this ADR, PR b): `tl_recipes.py` +
|
||
`softmax_merge` recipe + PE_SCHEDULER position-scan + DMA
|
||
auto-insertion + strict-FIFO RW tracker.
|
||
4. **ADR-0065 Phase 3** (this ADR, PR c): `_gqa_decode_long.py` opt2
|
||
variant + numeric parity test + dispatch-ratio measurement against
|
||
opt3 baseline.
|
||
|
||
Detailed implementation plan: see **DDD-0065**.
|