- name
- flydsl-kernel-code-cleanup
- description
- Clean up aiter FlyDSL kernels and shared helpers while preserving numerical behavior and performance. Use for raw-IR migrations, helper deduplication, dead-code removal, and reviews of those changes against the pinned FlyDSL API.
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# FlyDSL Kernel Code Cleanup
Maps legacy kernel constructs to the `fx.*` surface available in aiter's pinned
FlyDSL version. See the in-tree `flydsl-kernel-authoring` skill for API guidance.
**Golden rule:** in `@flyc.kernel` / `@flyc.jit` bodies, use `fx.*` and Python
operators first. Drop to a raw dialect only at a hard boundary with no wrapper,
and localize it.
Before applying the recipes, check `requirements.txt` and the imported FlyDSL
version and module path. A sibling FlyDSL checkout can expose newer APIs than
aiter supports. Kernel cleanup does not require a dependency bump or edits to
FlyDSL itself; honor the task's explicit version, architecture and single-/multi-
GPU scope.
## Aiter layout
| Location | Role |
|---|---|
| `aiter/ops/flydsl/kernels/` | `@flyc.kernel` device kernels and shared helpers (`tensor_shim.py`, `kernels_common.py`, …) |
| `aiter/ops/flydsl/*.py` | Launch wrappers, compile helpers, public op entry points |
| `op_tests/test_flydsl_*.py` | Top-level FlyDSL correctness / perf tests |
| `op_tests/flydsl_tests/` | Additional FlyDSL kernel tests |
Prefer `from aiter.ops.flydsl.kernels.tensor_shim import _run_compiled, ptr_arg`.
Reuse `tensor_shim.py` for compilation, cached dispatch and failure recovery.
`moe_kernels._run_compiled(exe, args)` is a tuple-argument adapter for existing
MoE/AOT callers; preserve that contract when consolidating launch code.
Reuse existing owners before adding helpers: `act.py` for activations;
`tensor_shim.py` for pointer/base/dtype extraction;
`kernels_common.py` for `LOG2E` and host or wrapping integer `ceildiv`; family common modules
for reductions and specialized memory operations. Prefer typed `fx.min`/`fx.max`
and `fx.ceildiv` where their signedness, NaN and overflow semantics match.
## Cautions
- **Surgical, behavior-preserving.** Migration is a refactor: minimal diffs, match
local style.
- **Don't mass-rewrite heavily-legacy kernels** unless asked (e.g.
`flash_attn_gfx950.py` uses `_scf.IfOp`/`_raw` pervasively). Clean what the task
touches.
- **Verify.** Offset/type/SSA changes can shift results. Compare before/after
numerics and generated code with `FLYDSL_RUNTIME_ENABLE_CACHE=0`; use a fresh
dump directory per specialization so one shape cannot overwrite another.
- **Raw boundaries are semantic.** Retain exact scope/ordering, volatile and
alias metadata, raw SSA contracts, or integer widths unsupported by the pinned
API. Record the specific reason; do not merely hide a dialect in a new facade.
---
## 1. `ArithValue` and index helpers (deprecated in `expr/arith.py`)
| Deprecated | Replacement |
|---|---|
| `ArithValue(x)` (wrap for operators) | `fx.Int32/Int64/Float32/Vector` — already overload `+ - * / % << >> == < >` |
| `arith.unwrap(v)` / `arith._to_raw(v)` | `v.ir_value()`, only where a raw `ir.Value` is needed |
| index-typed arithmetic counters | `fx.Int64(...)` or `fx.Int32(...)` when the consumer permits a fixed-width integer |
| `arith.index_cast(T.index, v)` at an index-typed boundary | `fx.Index(v)` |
`fx.Index` maps to MLIR `index`. Prefer explicit-width `fx.Int64`/`fx.Int32` for
arithmetic, choosing width and signedness deliberately. Keep `fx.Index` where a
launch, layout, loop or other API requires the index type; replacing it merely
to remove the name can change the IR contract. Do not widen `i32` counters or
narrow an index without checking the consumer and supported bounds.
```python
# Before
acc = ArithValue(val) + peer
lane = ArithValue(tid) % fx.Index(64)
cond = arith.unwrap(idx >= limit)
off = arith.index_cast(T.index, x)
# After
acc = val + peer # val already fx.Float32 / fx.Vector
lane = tid % fx.Int64(64)
cond = (idx >= limit).ir_value() # only if a raw scf.IfOp needs it
off = fx.Index(x) # preserve this consumer's index contract
```
If an operand is a raw `ir.Value`, wrap it once at the source (`fx.Float32(v)`),
not with `ArithValue` per use. Keep an explicit `arith.*FOp` only for non-default
fastmath.
### 1b. Drop redundant `fx.*` wraps
Wrap only to *introduce* a type (Python literal / raw `ir.Value`) or *change* one.
Re-wrapping an already-typed value is noise; double-wrapping is dead.
```python
# Before
for i in range_constexpr(fx.Int32(N)):
off = fx.Int64(fx.Int64(base) + fx.Int64(4))
tile = fx.make_layout(fx.Int32(BLOCK), fx.Int32(1))
idx = fx.Int32(tx) # tx already fx.Int32
# After
for i in range_constexpr(N):
off = base + fx.Int64(4)
tile = fx.make_layout(BLOCK, 1) # builders take Python ints
idx = tx
```
- Compile-time shapes/strides/bounds (`make_layout`, `make_shape`,
`range_constexpr`, `Constexpr`) take plain Python ints.
- Wrap a runtime value once, at first typed use.
- A real cast (`fx.Int64(i32)` widen, `fx.Int32(index)` narrow) is not redundant —
it replaces `arith.index_cast`.
### 1c. Thread and block IDs
In pinned FlyDSL 0.3.4.1, `fx.thread_idx.x` and `fx.block_idx.x` return
`fx.Int32` values. `gpu.thread_idx.x` and `gpu.block_idx.x` are the same
typed accessors. Direct `gpu.thread_id("x")` / `gpu.block_id("x")` calls
return raw MLIR values, so wrap those calls with `fx.Int32(...)` before typed
arithmetic. Do not label the typed accessors legacy or remove a cast from a
direct call merely because both spellings refer to the same GPU ID.
```python
tid = fx.thread_idx.x # already fx.Int32
bid = fx.block_idx.x # already fx.Int32
raw_tid = gpu.thread_id("x") # raw MLIR value
tid_from_raw = fx.Int32(raw_tid) # typed boundary
```
---
## 2. `buffer_ops` → `make_buffer_tensor` + copy atoms
`create_buffer_resource` + manual offsets is legacy. Build a buffer-resource view
with `fx.rocdl.make_buffer_tensor()`, then use layout ops + `fx.copy` (§7b).
Its default `max_size=True` leaves the record bound effectively unlimited;
choose `max_size=False` or `num_records_bytes=` for hardware OOB checking.
```python
# Before (manual offsets — see PA //4 offset bugs)
rsrc = buffer_ops.create_buffer_resource(A, max_size=True)
data = buffer_ops.buffer_load(rsrc, row * K + k, vec_width=4, dtype=fx.Float32)
buffer_ops.buffer_store(data, rsrc, row * N + col)
# After
bufA = fx.rocdl.make_buffer_tensor(A)
tA = fx.make_view(fx.get_iter(bufA), fx.make_layout((M, K), (K, 1)))
copy = fx.make_copy_atom(fx.rocdl.BufferCopy128b(), fx.Float32)
fx.copy(copy, fx.slice(tA, (None, tid)), rA) # after partitioning tA (§7b: prefer fx.copy)
```
- `make_buffer_tensor(tensor, max_size=True)` mirrors `create_buffer_resource`;
pass `num_records_bytes=` for a const byte count, or `max_size=False` to derive
from the layout.
- gfx1250 TDM uses a different atom — `fx.rocdl.make_tdm_atom` (raw VA, not a
buffer resource).
- A scalar-base + per-thread-offset load with no layout form may stay on
`buffer_ops` — note it. `buffer_load/store` `offset` is in **elements** (×
`sizeof(dtype)` internally) — a classic bug.
- aiter still ships `aiter/ops/flydsl/kernels/buffer_ops.py` for legacy kernels;
migrate off it when touching load/store paths.
---
## 3. Raw upstream dialects → `fx.*` and Python
### `arith`
| Raw | Preferred |
|---|---|
| `arith.constant(42, index=True)` | `fx.Int64(42)` |
| `arith.mulf/addf(a,b)` | `a * b` / `a + b` |
| `arith.trunc_f(ty, v)` / `ext_f` | `v.to(fx.BFloat16)` |
| `arith.index_cast(T.i32, v)` | `fx.Int32(v)` |
| `arith.select(cond, t, f)` | `cond.select(t, f)` |
| `arith.cmpi(slt, a, b)` | `a < b` |
| `arith.maximumf/minimumf(a,b)` | `fx.max(a, b)` / `fx.min(a, b)` |
| `arith.maxsi/maxui/minsi/minui(a,b)` | `fx.max(a, b)` / `fx.min(a, b)` |
| `arith.maxnumf(a,b)` | `fx.maxnumf(a, b)` — different NaN semantics from `fx.max` |
| `arith.ceildivsi/ceildivui(a,b)` | `fx.ceildiv(a, b)` |
| `math.fma(a,b,c)` | `fx.fma(a, b, c)` — preserves fused rounding |
| `math.absf(v)` | `fx.absf(v)` — check signed-zero/NaN behavior if replacing a select |
Keep `arith.cmpf` / explicit `*FOp` only where no operator exists or fastmath is
needed. Do not replace separate `a * b + c` operations with `fx.fma` unless
fused rounding is intended.
### `scf`
| Raw | Preferred |
|---|---|
| `scf.ForOp` | `range_constexpr(N)` (unrolled) or `range(lo, hi, step, init=[...])` (runtime, loop-carried) |
| `scf.IfOp(_raw(cond))` | Python `if cond:` (runtime) / `if const_expr(flag):` (compile-time) |
Check the rewriter's loop contract in pinned FlyDSL 0.3.4.1:
- `range_constexpr` requests Python unrolling.
- `range(..., init=[...])` emits an `scf.for` with explicit carried state and
converts its bounds to index, including Python integer bounds. It does not
discard `init` merely because the bounds are static.
- Ordinary `range` without `init` uses automatic carried-state dispatch and
expects `i32` bounds; index bounds are converted to `i32`, and `i64` is rejected.
Preserve the selected loop form, supported bounds and state types. See §5 for
runtime branches inside helper functions.
### `vector`
| Raw | Preferred |
|---|---|
| `vector.extract(v, static_position=[i])` | `fx.Vector(v)[i]` |
| `vector.bitcast(ty, v)` | `fx.Vector(v).bitcast(fx.Float32)` |
| `vector.splat` / const vector | `fx.Vector.filled(width, val, fx.Float32)` |
| build from scalars | `fx.Vector.from_elements(...)` |
| reg-memref load/store | `fx.memref_load_vec(r)` / `fx.memref_store_vec(v, r)` |
### `llvm` / `memref` / `math`
- `llvm.*` ptr math / load/store / const → layout views (`fx.make_view`,
`fx.get_iter`), `fx.Array` + `SharedAllocator`, `fx` constants. Use existing
intrinsic wrappers where equivalent; keep unsupported boundaries local to
aiter rather than extending FlyDSL as part of a cleanup.
- `memref.*` → layout tensors/views + copy atoms.
- `math.*` → `fx` math helpers (`expr/math.py`); keep `math_dialect.fma` etc. only
where no wrapper exists.
### 3b. `fly.ptr` → `!llvm.ptr` (backend-resolved address space)
When you hold an `fx` pointer (`fly.ptr`) and need a raw `!llvm.ptr` at a hard
boundary, use the DSL primitive — it maps the pointer's semantic address space to
the backend's LLVM address-space number for you. Don't hand-build one with a
hardcoded `<1>` / `<3>` via `IntToPtrOp`.
```python
# Before (hardcoded address space)
p = buffer_ops.create_llvm_ptr(lds_addr, address_space=3)
p = mem_ops._create_llvm_ptr(val, address_space=1) # a.k.a. mem_ops.to_llvm_ptr
# After
p = ptr.llvm_ptr # property on an fx pointer
p = fx.to_llvm_ptr(ptr) # equivalent free function; backend resolves the AS
```
- For a raw integer address, construct a semantic `fly.ptr` with public
`fx.inttoptr`, then convert it with `fx.to_llvm_ptr` only if the downstream
operation truly needs `!llvm.ptr`:
```python
ty = fx.PointerType.get(fx.Int32.ir_type, fx.AddressSpace.Global, 4)
ptr = fx.inttoptr(ty, fx.Int64(address))
llvm_ptr = fx.to_llvm_ptr(ptr)
```
Choose the correct address space, element type, and proven alignment. A raw
byte address for LDS uses `fx.AddressSpace.Shared` instead.
- `mem_ops.get_llvm_ptr` / `element_ptr` also fold in `+ offset*dtype_bytes`
arithmetic; keep the offset math (layout views / `get_element_ptr`) and only swap
the final ptr cast for `.llvm_ptr`.
- Preserve byte versus element GEPs and alignment provenance. An equal numeric
address alone does not guarantee equal memory instructions; compare the
generated loads and stores when replacing an epilog pointer path.
### 3c. Manual `s_waitcnt` bitfields → `fx.rocdl.s_waitcnt(vmcnt=/lgkmcnt=/expcnt=)`
Hand-encoding a wait-counter bitfield (or calling `rocdl.s_waitcnt(magic)` with a
raw number) is arch-fragile — the field widths differ per arch (CDNA3 `lgkmcnt`
max 15 vs RDNA 63). The keyword form of `fx.rocdl.s_waitcnt`
(`expr/rocdl/universal.py`) packs target-specific bitfields for gfx942,
gfx950, gfx11xx, and gfx120x. **Pinned 0.3.4.1 rejects gfx1250** here; do
not migrate a gfx1250 wait to this API. Use the target's supported wait ops
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