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[BACKEND][PPU] Add INT8 AIU support to PPU0010 V1 lowering
1 parent 11e9e34 commit b20e5b2

4 files changed

Lines changed: 246 additions & 25 deletions

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third_party/ppu/lib/TritonPPUGPUToLLVM/AIUUtility.cpp

Lines changed: 17 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -204,13 +204,14 @@ DenseMap<unsigned, Value> getPPUAIUV1SwizzledSharedPtrs(
204204
/*withCTAOffset=*/false);
205205

206206
auto aiuLoad = resSharedLayout.getAIUStrategy();
207+
unsigned elemBytes = resElemTy.getIntOrFloatBitWidth() / 8;
207208
unsigned cubeC = aiuLoad[0];
208209
unsigned cubeW = aiuLoad[1];
209210
unsigned aiuWarpCopyC = aiuLoad[2];
210211
unsigned aiuWarpCopyW = aiuLoad[3];
211-
unsigned minVec = std::min(outVec, inVec);
212-
unsigned elemsPerSlice =
213-
16 * cubeW; // 32/(resElemTy.getIntOrFloatBitWidth()/8) * cubeW;
212+
unsigned minVec = std::min(16 / elemBytes, inVec);
213+
unsigned sliceElems = 32 / elemBytes;
214+
unsigned elemsPerSlice = sliceElems * cubeW;
214215
unsigned elemsPerCopy = cubeC * cubeW * aiuWarpCopyC * aiuWarpCopyW;
215216
unsigned elemsPerCube = cubeC * cubeW;
216217

@@ -242,7 +243,7 @@ DenseMap<unsigned, Value> getPPUAIUV1SwizzledSharedPtrs(
242243
// copy index inside tensor
243244
Value copyIdx = b.udiv(idxColCube, b.i32_val(aiuWarpCopyC));
244245
// slice ID inside cube
245-
Value sliceID = b.udiv(idxColInnerCube, b.i32_val(16));
246+
Value sliceID = b.udiv(idxColInnerCube, b.i32_val(sliceElems));
246247
// slice offset inside cube
247248
Value sliceOffset = b.mul(sliceID, b.i32_val(elemsPerSlice));
248249
// warp offset inside copy
@@ -256,18 +257,17 @@ DenseMap<unsigned, Value> getPPUAIUV1SwizzledSharedPtrs(
256257
Value sliceStartPtr =
257258
b.gep(dstPtrTy, resElemTy, dstPtrBase, sliceStartOffset);
258259

259-
// column index inside slice, slice shape is (cubeW, 16)
260-
Value idxColInnerSlice = b.urem(idxColInnerCube, b.i32_val(16));
260+
Value idxColInnerSlice =
261+
b.urem(idxColInnerCube, b.i32_val(sliceElems));
261262
// new swizzled row index inside slice, swizzled slice shape is (cubeW/4,
262263
// 64)
263264
Value rowSwizzleID = b.udiv(idxRowInnerCube, b.i32_val(4));
264265
// new linear slice index inside slice, slice shape is (cubeW/4, 64)
265-
Value idxColSlicelinear =
266-
b.urem(b.add(b.mul(idxRowInnerCube, b.i32_val(16)), idxColInnerSlice),
267-
b.i32_val(64));
268-
// new column slice ID, fp16, vec=8
269-
// Value colSliceID = lshr(idxColSlicelinear, i32_val(3));
270-
Value colSliceID = b.udiv(idxColSlicelinear, b.i32_val(8));
266+
Value idxColSlicelinear = b.urem(
267+
b.add(b.mul(idxRowInnerCube, b.i32_val(sliceElems)), idxColInnerSlice),
268+
b.i32_val(128 / elemBytes));
269+
Value colSliceID =
270+
b.udiv(idxColSlicelinear, b.i32_val(16 / elemBytes));
271271

272272
// rotated length: (((sliceID>1)|(sliceID<1))&0x3) << 1
273273
// sliceID 0, 1, 2, 3 ---> rotated length: 0, 4, 2, 6
@@ -284,11 +284,13 @@ DenseMap<unsigned, Value> getPPUAIUV1SwizzledSharedPtrs(
284284
Value colRotID = b.sub(b.i32_val(7), colRotBitPos);
285285
Value colSwizzleID = b.xor_(colRotID, b.urem(rowSwizzleID, b.i32_val(2)));
286286

287-
Value swizzleOffset = b.add(b.mul(rowSwizzleID, b.i32_val(64)),
288-
b.mul(colSwizzleID, b.i32_val(8)));
287+
Value swizzleOffset = b.add(
288+
b.mul(rowSwizzleID, b.i32_val(128 / elemBytes)),
289+
b.mul(colSwizzleID, b.i32_val(16 / elemBytes)));
289290

290291
// for minVec is not equal to outVec
291-
swizzleOffset = b.or_(swizzleOffset, b.urem(idxCol, b.i32_val(8)));
292+
swizzleOffset = b.or_(
293+
swizzleOffset, b.urem(idxCol, b.i32_val(16 / elemBytes)));
292294
ret[elemIdx] = b.gep(dstPtrTy, resElemTy, sliceStartPtr, swizzleOffset);
293295
}
294296

third_party/ppu/lib/TritonPPUGPUToLLVM/ConvertLayoutOpToLLVM/SharedToDotOperandPPUAIUV1.cpp

Lines changed: 47 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -37,10 +37,53 @@ using ::mlir::triton::gpu::PPUAIUSharedEncodingAttr;
3737

3838
namespace SharedToDotOperandPPUAIUV1 {
3939

40+
static Value callIntrinsic(ConversionPatternRewriter &rewriter, Location loc,
41+
StringRef name, Type resultTy, ValueRange args) {
42+
Type funcType = mlir::triton::gpu::getFunctionType(resultTy, args);
43+
LLVM::LLVMFuncOp func = mlir::triton::gpu::appendOrGetExternFuncOp(
44+
rewriter, rewriter.getInsertionBlock()->getParentOp(), name, funcType);
45+
return LLVM::createLLVMCallOp(rewriter, loc, func, args).getResult();
46+
}
47+
48+
static std::tuple<Value, Value, Value, Value>
49+
loadX4B8(ConversionPatternRewriter &rewriter, Location loc, Value smemBase,
50+
Value startCoordY, Value startCoordX, Value blockLineStride,
51+
Value channelOffset, bool needTrans) {
52+
auto b = TritonLLVMOpBuilder(loc, rewriter);
53+
if (needTrans)
54+
llvm::report_fatal_error(
55+
"PPU0010 B8 AIU dot requires native A-row/B-col layout");
56+
Value bytePtr = b.bitcast(smemBase, ptr_ty(rewriter.getContext(), 3));
57+
Value topLeftIndex =
58+
b.add(b.mul(startCoordY, blockLineStride), startCoordX);
59+
Value sliceId = b.udiv(channelOffset, b.i32_val(32));
60+
Value sliceOffset = b.mul(sliceId, b.mul(blockLineStride, b.i32_val(32)));
61+
bytePtr = b.gep(ptr_ty(rewriter.getContext(), 3), i8_ty,
62+
bytePtr, sliceOffset);
63+
Value sBase = b.or_(
64+
b.shl(b.and_(sliceId, b.i32_val(3)), b.i32_val(27)),
65+
b.or_(b.shl(b.and_(blockLineStride, b.i32_val(0x7ff)), b.i32_val(16)),
66+
b.and_(topLeftIndex, b.i32_val(0xffff))));
67+
auto resultTy = vec_ty(i32_ty, 4);
68+
Value loaded = callIntrinsic(rewriter, loc,
69+
"llvm.ppu.tsm.ld.swizzle.b32x4.p3i8",
70+
resultTy, {bytePtr, b.i32_val(1), sBase});
71+
Value r0 = b.extract_element(i32_ty, loaded, b.i32_val(0));
72+
Value r1 = b.extract_element(i32_ty, loaded, b.i32_val(1));
73+
Value r2 = b.extract_element(i32_ty, loaded, b.i32_val(2));
74+
Value r3 = b.extract_element(i32_ty, loaded, b.i32_val(3));
75+
return {r0, r1, r2, r3};
76+
}
77+
4078
std::tuple<Value, Value, Value, Value>
4179
loadX4(ConversionPatternRewriter &rewriter, Location loc, Value smemBase,
4280
Value start_coord_y, Value start_coord_x, Value cube_h, Value cube_w,
43-
Value cube_n, Value channel_offset, Type matTy, bool needTrans) {
81+
Value cube_n, Value channel_offset, Type matTy, bool needTrans,
82+
int elemBytes) {
83+
if (elemBytes == 1)
84+
return loadX4B8(rewriter, loc, smemBase, start_coord_y, start_coord_x,
85+
cube_w, channel_offset, needTrans);
86+
4487
auto b = TritonLLVMOpBuilder(loc, rewriter);
4588
// The struct should have exactly the same element types.
4689
auto resTy = cast<LLVM::LLVMStructType>(matTy);
@@ -177,6 +220,8 @@ std::function<void(int, int, int)> getLoadMatrixFn(
177220
unsigned replicaK = b >> 1;
178221
unsigned replicaMNElements = shapePerWarpM * warpsPerTile;
179222
unsigned replicaKElements = 16;
223+
if (elemBytes == 1)
224+
replicaKElements = 32;
180225
unsigned replicaMNOff = replicaMNElements * replicaMN;
181226
unsigned replicaKOff = replicaKElements * replicaK;
182227

@@ -274,7 +319,7 @@ std::function<void(int, int, int)> getLoadMatrixFn(
274319
// actually load from shared memory
275320
auto [ha0, ha1, ha2, ha3] =
276321
loadX4(rewriter, loc, smemBase, start_coord_y, start_coord_x, cube_h,
277-
cube_w, cube_n, channel_offset, matTy, needTrans);
322+
cube_w, cube_n, channel_offset, matTy, needTrans, elemBytes);
278323

279324
vals[{batch, a, b}] = ha0;
280325
vals[{batch, a, b + 1}] = ha1;

third_party/ppu/lib/TritonPPUGPUToLLVM/LoadStoreOpToLLVM.cpp

Lines changed: 6 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -570,7 +570,7 @@ struct StoreOpConversion : public ConvertOpToLLVMPattern<triton::StoreOp>,
570570
bool isSharedStore = isSharedMemoryPointer(ptrElems[vecStart]);
571571

572572
auto &tixStoreInstr =
573-
tixBuilder.create("ppu.st")
573+
tixBuilder.create(isSharedStore ? "ppu.st" : "st")
574574
->o("global", !isSharedStore)
575575
.o("shared", isSharedStore)
576576
.o("wb",
@@ -689,15 +689,16 @@ struct AsyncAIUCopyGlobalToLocalOpConversion
689689

690690
unsigned numCopies = tileC / channelElemsPerCTA;
691691
//@$0
692+
std::string dtype = (elementSizeInBytes == 1) ? ".b8" : ".b16";
692693
std::string aiuInst =
693694
"ppu.cp.async.aiu.bulk.tensor.shared.global.padz.swzl.zfill." +
694-
std::to_string(rank) +
695-
"d.b16 [$0], [$1], {$2, $3, $4, $5, $6, $7}, {$8, $9, $10, $11};";
695+
std::to_string(rank) + "d" + dtype +
696+
" [$0], [$1], {$2, $3, $4, $5, $6, $7}, {$8, $9, $10, $11};";
696697
if (isNeedPred) {
697698
aiuInst =
698699
"@$0 ppu.cp.async.aiu.bulk.tensor.shared.global.padz.swzl.zfill." +
699-
std::to_string(rank) +
700-
"d.b16 [$1], [$2], {$3, $4, $5, $6, $7, $8}, {$9, $10, $11, $12};";
700+
std::to_string(rank) + "d" + dtype +
701+
" [$1], [$2], {$3, $4, $5, $6, $7, $8}, {$9, $10, $11, $12};";
701702
}
702703
for (int copyIdx = 0; copyIdx < numCopies; copyIdx++) {
703704
Value xOffset = b.add(xCoord, b.mul(warpIdxM, b.i32_val(cubeWElems)));

third_party/ppu/python/test/unit/tle/test_tle_aiu_async_load.py

Lines changed: 176 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -18,8 +18,10 @@
1818
import re
1919
import shutil
2020
import pytest
21+
import torch
2122
import triton
2223
import triton.language as tl
24+
from triton import knobs
2325
from triton.backends.compiler import GPUTarget
2426

2527
tle_backend = pytest.importorskip(
@@ -44,9 +46,22 @@ def _ppu_sdk_available() -> bool:
4446
_skip_no_sdk = pytest.mark.skipif(not _ppu_sdk_available(), reason="PPU SDK not available")
4547

4648

47-
def _compile(kernel, signature, constexprs, target=None):
49+
def _compile(kernel, signature, constexprs, target=None, options=None):
4850
src = triton.compiler.ASTSource(fn=kernel, signature=signature, constexprs=constexprs)
49-
return triton.compile(src, target=target or _GPU_TARGET)
51+
return triton.compile(src, target=target or _GPU_TARGET, options=options)
52+
53+
54+
def _compile_through_llir(kernel, signature, constexprs, target=None, options=None):
55+
previous_hook = knobs.runtime.add_stages_inspection_hook
56+
57+
def stop_before_hgbin(_backend, stages, _options, _language, _capability):
58+
stages["hgbin"] = lambda _src, _metadata: b""
59+
60+
knobs.runtime.add_stages_inspection_hook = stop_before_hgbin
61+
try:
62+
return _compile(kernel, signature, constexprs, target, options)
63+
finally:
64+
knobs.runtime.add_stages_inspection_hook = previous_hook
5065

5166

5267
def _assert_stages_exist(compiled, stages=("ttir", "ttgir", "llir")):
@@ -60,6 +75,17 @@ def _assert_no_tle_residue(compiled):
6075
assert not leak, f"residual tle.* ops in LLIR:\n" + "\n".join(leak[:5])
6176

6277

78+
def _assert_int8_uses_ppu_aiu_v1_b8(compiled):
79+
ttgir = compiled.asm["ttgir"]
80+
llir = compiled.asm["llir"]
81+
aiu_instructions = [line for line in llir.splitlines() if "ppu.cp.async.aiu" in line]
82+
assert "versionMajor = 1" in ttgir
83+
assert aiu_instructions, "expected an async AIU copy instruction"
84+
assert all(".2d.b8" in line for line in aiu_instructions)
85+
assert all(".b8" in line for line in aiu_instructions)
86+
assert all(".b16" not in line for line in aiu_instructions)
87+
88+
6389
# ---------------------------------------------------------------------------
6490
# 1. Basic promotion & fallback
6591
# ---------------------------------------------------------------------------
@@ -144,6 +170,37 @@ def test_aiu_promotion_dtypes(dtype):
144170
_assert_stages_exist(compiled)
145171
assert "aiu_load" in compiled.asm["ttir"]
146172
_assert_no_tle_residue(compiled)
173+
if dtype == "fp32":
174+
aiu_instructions = [
175+
line for line in compiled.asm["llir"].splitlines()
176+
if "ppu.cp.async.aiu" in line
177+
]
178+
assert aiu_instructions
179+
assert all(".b16" in line for line in aiu_instructions)
180+
assert all(".b8" not in line for line in aiu_instructions)
181+
182+
183+
@_skip_no_sdk
184+
def test_int8_aiu_load_uses_v1_b8_instruction():
185+
compiled = _compile_through_llir(_typed_aiu_load, {"a_ptr": "*i8", "c_ptr": "*i8"},
186+
{"M": 256, "K": 256, "BLOCK_M": 64, "BLOCK_K": 64})
187+
_assert_stages_exist(compiled)
188+
assert "aiu_load" in compiled.asm["ttir"]
189+
_assert_no_tle_residue(compiled)
190+
_assert_int8_uses_ppu_aiu_v1_b8(compiled)
191+
192+
193+
@_skip_no_sdk
194+
@pytest.mark.skipif(not torch.cuda.is_available(), reason="PPU device not available")
195+
def test_int8_aiu_load_device_correctness():
196+
expected = torch.arange(32 * 32, device="cuda", dtype=torch.int32)
197+
expected = expected.remainder(127).to(torch.int8).reshape(32, 32)
198+
actual = torch.empty_like(expected)
199+
_typed_aiu_load[(1,)](
200+
expected, actual, 32, 32, 32, 32, num_warps=4, num_stages=1
201+
)
202+
torch.cuda.synchronize()
203+
torch.testing.assert_close(actual.cpu(), expected.cpu(), rtol=0, atol=0)
147204

148205

149206
# ---------------------------------------------------------------------------
@@ -231,6 +288,94 @@ def _gemm_aiu_kernel(
231288
_GEMM_CONSTEXPRS = {"M": 512, "N": 512, "K": 256, "BLOCK_M": 64, "BLOCK_N": 64, "BLOCK_K": 64}
232289

233290

291+
@triton.jit(do_not_specialize_on_alignment=["a_ptr", "b_ptr", "c_ptr"])
292+
def _int8_gemm_aiu_kernel(
293+
a_ptr,
294+
b_ptr,
295+
c_ptr,
296+
M: tl.constexpr,
297+
N: tl.constexpr,
298+
K: tl.constexpr,
299+
BLOCK_M: tl.constexpr,
300+
BLOCK_N: tl.constexpr,
301+
BLOCK_K: tl.constexpr,
302+
):
303+
pid_m = tl.program_id(0)
304+
pid_n = tl.program_id(1)
305+
a_bp = tl.make_block_ptr(a_ptr, shape=(M, K), strides=(K, 1),
306+
offsets=(pid_m * BLOCK_M, 0),
307+
block_shape=(BLOCK_M, BLOCK_K), order=(1, 0))
308+
# b_ptr is physically contiguous [N, K], logically column-major [K, N].
309+
b_bp = tl.make_block_ptr(b_ptr, shape=(K, N), strides=(1, K),
310+
offsets=(0, pid_n * BLOCK_N),
311+
block_shape=(BLOCK_K, BLOCK_N), order=(0, 1))
312+
acc = tl.zeros((BLOCK_M, BLOCK_N), dtype=tl.int32)
313+
for _ in range(0, K, BLOCK_K):
314+
a = tle.load(a_bp, is_async=True)
315+
b = tle.load(b_bp, is_async=True)
316+
acc += tl.dot(a, b)
317+
a_bp = tl.advance(a_bp, (0, BLOCK_K))
318+
b_bp = tl.advance(b_bp, (BLOCK_K, 0))
319+
offs_m = pid_m * BLOCK_M + tl.arange(0, BLOCK_M)
320+
offs_n = pid_n * BLOCK_N + tl.arange(0, BLOCK_N)
321+
tl.store(c_ptr + N * offs_m[:, None] + offs_n[None, :], acc,
322+
mask=(offs_m[:, None] < M) & (offs_n[None, :] < N))
323+
324+
325+
@_skip_no_sdk
326+
def test_int8_gemm_uses_v1_b8_aiu_load_and_int8_mma():
327+
compiled = _compile_through_llir(
328+
_int8_gemm_aiu_kernel,
329+
{"a_ptr": "*i8", "b_ptr": "*i8", "c_ptr": "*i32"},
330+
_GEMM_CONSTEXPRS,
331+
options={"num_stages": 2},
332+
)
333+
llir = compiled.asm["llir"]
334+
aiu_instructions = [line for line in llir.splitlines() if "ppu.cp.async.aiu" in line]
335+
assert len(aiu_instructions) >= 2
336+
assert all(".2d.b8" in line for line in aiu_instructions)
337+
assert llir.count("llvm.ppu.tsm.ld.swizzle.b32x4.p3i8") >= 2
338+
assert "ldmatrix.sync.aligned.m8n8.x4.swzl.shared.b8" not in llir
339+
assert "ldmatrix.sync.aligned.m16n16.x1.swzl.trans.shared.b8" not in llir
340+
assert "llvm.ppu.mat.trans.b8" not in llir
341+
assert "ppu.mma.sync.aligned.m16n16k32.row.col.satfinite.s32.s8.s8.s32" in llir
342+
343+
344+
@_skip_no_sdk
345+
@pytest.mark.skipif(not torch.cuda.is_available(), reason="PPU device not available")
346+
@pytest.mark.parametrize(
347+
"m,n,k,bm,bn,bk,num_warps",
348+
[(16, 16, 32, 16, 16, 32, 1),
349+
(16, 32, 64, 16, 32, 64, 1),
350+
(64, 64, 64, 64, 64, 64, 4),
351+
(128, 128, 128, 64, 64, 64, 4)],
352+
)
353+
def test_int8_gemm_aiu_device_correctness(m, n, k, bm, bn, bk, num_warps):
354+
torch.manual_seed(123)
355+
a = torch.randint(-8, 9, (m, k), device="cuda", dtype=torch.int8)
356+
b = torch.randint(-8, 9, (n, k), device="cuda", dtype=torch.int8)
357+
actual = torch.empty((m, n), device="cuda", dtype=torch.int32)
358+
grid = (triton.cdiv(m, bm), triton.cdiv(n, bn))
359+
_int8_gemm_aiu_kernel[grid](a, b, actual, m, n, k, bm, bn, bk,
360+
num_warps=num_warps, num_stages=1)
361+
torch.cuda.synchronize()
362+
expected = a.cpu().to(torch.int32) @ b.cpu().to(torch.int32).T
363+
torch.testing.assert_close(actual.cpu(), expected, rtol=0, atol=0)
364+
365+
366+
@_skip_no_sdk
367+
def test_global_store_uses_sdk_opcode_spelling():
368+
compiled = _compile_through_llir(
369+
_int8_gemm_aiu_kernel,
370+
{"a_ptr": "*i8", "b_ptr": "*i8", "c_ptr": "*i32"},
371+
_GEMM_CONSTEXPRS,
372+
options={"num_stages": 2},
373+
)
374+
llir = compiled.asm["llir"]
375+
assert "st.global" in llir
376+
assert "ppu.st.global" not in llir
377+
378+
234379
@_skip_no_sdk
235380
def test_gemm_aiu_both_operands_promoted():
236381
"""Both A and B matrix loads should be promoted to AIULoadOp."""
@@ -300,10 +445,38 @@ def kernel(a_ptr, c_ptr, M: tl.constexpr, K: tl.constexpr, BLOCK_M: tl.constexpr
300445
mask=(offs_m[:, None] < M) & (offs_k[None, :] < K))
301446

302447
compiled = _compile(kernel, {"a_ptr": "*fp16", "c_ptr": "*fp16"},
303-
{"M": 512, "K": 512, "BLOCK_M": 64, "BLOCK_K": 64})
448+
{"M": 512, "K": 512, "BLOCK_M": 64, "BLOCK_K": 64},
449+
options={"num_stages": num_stages})
450+
_assert_stages_exist(compiled)
451+
assert "aiu_load" in compiled.asm["ttir"]
452+
_assert_no_tle_residue(compiled)
453+
454+
455+
@_skip_no_sdk
456+
def test_int8_aiu_pipelined_loop_uses_v1_b8_instruction():
457+
458+
@triton.jit
459+
def kernel(a_ptr, c_ptr, M: tl.constexpr, K: tl.constexpr, BLOCK_M: tl.constexpr, BLOCK_K: tl.constexpr):
460+
pid = tl.program_id(0)
461+
a_bp = tl.make_block_ptr(a_ptr, shape=(M, K), strides=(K, 1), offsets=(pid * BLOCK_M, 0),
462+
block_shape=(BLOCK_M, BLOCK_K), order=(1, 0))
463+
acc = tl.zeros((BLOCK_M, BLOCK_K), dtype=tl.int32)
464+
for _ in range(0, K, BLOCK_K):
465+
a = tle.load(a_bp, is_async=True)
466+
acc += a.to(tl.int32)
467+
a_bp = tl.advance(a_bp, (0, BLOCK_K))
468+
offs_m = pid * BLOCK_M + tl.arange(0, BLOCK_M)
469+
offs_k = tl.arange(0, BLOCK_K)
470+
tl.store(c_ptr + K * offs_m[:, None] + offs_k[None, :], acc,
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mask=(offs_m[:, None] < M) & (offs_k[None, :] < K))
472+
473+
compiled = _compile_through_llir(kernel, {"a_ptr": "*i8", "c_ptr": "*i32"},
474+
{"M": 512, "K": 512, "BLOCK_M": 64, "BLOCK_K": 64},
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options={"num_stages": 2})
304476
_assert_stages_exist(compiled)
305477
assert "aiu_load" in compiled.asm["ttir"]
306478
_assert_no_tle_residue(compiled)
479+
_assert_int8_uses_ppu_aiu_v1_b8(compiled)
307480

308481

309482
# ---------------------------------------------------------------------------

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