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[AMD] Support ds3.2 on gfx942 platform (#17504)

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Co-authored-by: Hubert Lu <55214931+hubertlu-tw@users.noreply.github.com>
This commit is contained in:
wufann
2026-01-22 13:57:08 -08:00
committed by GitHub
co-authored by Hubert Lu
parent 15b511771d
commit a921029b97
4 changed files with 135 additions and 78 deletions
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docker/rocm.Dockerfile
+23 -3
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@@ -69,6 +69,10 @@ ARG TILELANG_REPO="https://github.com/HaiShaw/tilelang.git"
ARG TILELANG_BRANCH="dsv32-mi35x"
ARG TILELANG_COMMIT="ae938cf885743f165a19656d1122ad42bb0e30b8"
ARG TILELANG_GFX942_REPO="https://github.com/tile-ai/tilelang.git"
ARG TILELANG_GFX942_BRANCH="main"
ARG TILELANG_GFX942_COMMIT="2d8d3676eda18bd3d8e6fa783399ff96d3cd4ded"
ARG FHT_REPO="https://github.com/jeffdaily/fast-hadamard-transform.git"
ARG FHT_BRANCH="rocm"
ARG FHT_COMMIT="46efb7d776d38638fc39f3c803eaee3dd7016bd1"
@@ -215,12 +219,13 @@ ENV LIBGL_ALWAYS_INDIRECT=1
RUN echo "LC_ALL=en_US.UTF-8" >> /etc/environment
RUN /bin/bash -lc 'set -euo pipefail; \
# Build TileLang only for gfx950
if [ "${GPU_ARCH:-}" != "gfx950" ]; then \
# Build TileLang for gfx950 and gfx942-rocm700
if [ "${GPU_ARCH:-}" != "gfx950" ] && [ "${GPU_ARCH:-}" != "gfx942-rocm700" ]; then \
echo "[TileLang] Skipping (GPU_ARCH=${GPU_ARCH:-unset})"; \
exit 0; \
fi; \
echo "[TileLang] Building TileLang for ${GPU_ARCH}"; \
if [ "$GPU_ARCH" = "gfx950" ]; then \
\
# System dependencies (NO llvm-dev to avoid llvm-config-16 shadowing)
apt-get update && apt-get install -y --no-install-recommends \
@@ -274,7 +279,22 @@ RUN /bin/bash -lc 'set -euo pipefail; \
git checkout -f "${TILELANG_COMMIT}" && \
git submodule update --init --recursive && \
export CMAKE_ARGS="-DLLVM_CONFIG=${LLVM_CONFIG} ${CMAKE_ARGS:-}" && \
bash ./install_rocm.sh'
bash ./install_rocm.sh; \
else \
# Build GoogleTest static libs (Ubuntu package ships sources only)
apt-get install -y libgtest-dev libgmock-dev && \
cmake -S /usr/src/googletest -B /tmp/build-gtest -DBUILD_GTEST=ON -DBUILD_GMOCK=ON -DCMAKE_BUILD_TYPE=Release && \
cmake --build /tmp/build-gtest -j && \
cp -v /tmp/build-gtest/lib/*.a /usr/lib/x86_64-linux-gnu/ && \
rm -rf /tmp/build-gtest; \
# Build TileLang for gfx942-rocm700
git clone --branch "${TILELANG_GFX942_BRANCH}" "${TILELANG_GFX942_REPO}" /opt/tilelang && \
cd /opt/tilelang && \
git checkout -f "${TILELANG_GFX942_COMMIT}" && \
git submodule update --init --recursive && \
sed -i "/^[[:space:]]*\"torch/d" pyproject.toml && \
USE_ROCM=1 USE_CUDA=0 pip install -e . -v ; \
fi'
# -----------------------
# Hadamard-transform (HIP build)
python/sglang/srt/layers/attention/nsa/index_buf_accessor.py
+12 -2
View File
@@ -4,8 +4,12 @@ import torch
import triton
import triton.language as tl
from sglang.srt.layers.quantization.fp8_kernel import is_fp8_fnuz
from sglang.srt.utils import is_hip
_is_hip = is_hip()
_is_fp8_fnuz = is_fp8_fnuz()
if TYPE_CHECKING:
from sglang.srt.mem_cache.memory_pool import NSATokenToKVPool
@@ -349,20 +353,23 @@ def _set_k_and_s_triton(
raise ValueError(
f"index_k_scale must be 1D or 2D, got shape {index_k_scale.shape}"
)
if is_hip():
if _is_hip:
assert buf_numel_per_page == 1 * (128 + 4)
else:
assert buf_numel_per_page == 64 * (128 + 4)
assert num_tokens_to_write == num_tokens_to_write_ == num_tokens_to_write__
assert index_head_dim == 128
assert scale_dim == 1
if is_hip():
if _is_hip:
assert page_size == 1
else:
assert page_size == 64
assert buf.dtype == torch.uint8
assert loc.dtype == torch.int64, f"{loc.dtype=}" # can be int32
if _is_fp8_fnuz:
assert index_k.dtype == torch.float8_e4m3fnuz
else:
assert index_k.dtype == torch.float8_e4m3fn
assert index_k_scale.dtype == torch.float32
@@ -371,6 +378,9 @@ def _set_k_and_s_triton(
assert index_k.is_contiguous()
assert index_k_scale.is_contiguous()
if _is_fp8_fnuz:
buf_fp8 = buf.view(torch.float8_e4m3fnuz)
else:
buf_fp8 = buf.view(torch.float8_e4m3fn)
buf_fp32 = buf.view(torch.float32)
python/sglang/srt/layers/attention/nsa/nsa_indexer.py
+10 -5
View File
@@ -8,6 +8,7 @@ import torch
from einops import rearrange
from sglang.srt.layers.layernorm import LayerNorm
from sglang.srt.layers.quantization.fp8_kernel import is_fp8_fnuz
from sglang.srt.layers.utils import MultiPlatformOp
from sglang.srt.utils import add_prefix, ceil_align, is_cuda, is_hip, is_npu
@@ -15,6 +16,7 @@ global _use_multi_stream
_is_cuda = is_cuda()
_is_hip = is_hip()
_is_npu = is_npu()
_is_fp8_fnuz = is_fp8_fnuz()
if _is_cuda:
try:
import deep_gemm
@@ -504,7 +506,9 @@ class Indexer(MultiPlatformOp):
)
k_fp8_list.append(k_fp8)
k_scale_list.append(k_scale)
if _is_fp8_fnuz:
k_fp8 = torch.cat(k_fp8_list, dim=0).view(torch.float8_e4m3fnuz)
else:
k_fp8 = torch.cat(k_fp8_list, dim=0).view(torch.float8_e4m3fn)
k_scale = torch.cat(k_scale_list, dim=0).view(torch.float32).squeeze(-1)
kv_fp8 = (k_fp8, k_scale)
@@ -569,9 +573,9 @@ class Indexer(MultiPlatformOp):
from aiter.ops.triton.fp8_mqa_logits import fp8_mqa_logits
kv, scale = kv_fp8
logits = fp8_mqa_logits(
logits_chunk = fp8_mqa_logits(
q_fp8[start:end],
kv_fp8,
kv,
scale,
weights[start:end],
ks[start:end],
@@ -1001,11 +1005,12 @@ class Indexer(MultiPlatformOp):
.view(m, ng, group)
.mul_(x_s.to(torch.float32).unsqueeze(-1))
.view(m, n)
.to(torch.bfloat16)
)
else:
x_for_gate = x_q.to(torch.float32)
x_for_gate = x_q.to(torch.bfloat16)
else:
x_for_gate = x_q.to(torch.float32)
x_for_gate = x_q.to(torch.bfloat16)
else:
x_for_gate = x
python/sglang/srt/layers/attention/nsa/tilelang_kernel.py
+30 -8
View File
@@ -4,21 +4,28 @@ import tilelang
import tilelang.language as T
import torch
from sglang.srt.utils import is_hip
from sglang.srt.layers.quantization.fp8_kernel import is_fp8_fnuz
from sglang.srt.utils import is_gfx95_supported, is_hip
tilelang.set_log_level("WARNING")
pass_configs = {
tilelang.PassConfigKey.TL_DISABLE_WARP_SPECIALIZED: True,
tilelang.PassConfigKey.TL_DISABLE_TMA_LOWER: True,
tilelang.PassConfigKey.TL_DISABLE_FAST_MATH: True,
}
BF16 = "bfloat16"
FP8 = "float8_e4m3"
FP32 = "float32"
# TL_DISABLE_FAST_MATH has deprecated in v0.1.7.post1 tilelang
if hasattr(tilelang.PassConfigKey, "TL_DISABLE_FAST_MATH"):
pass_configs[tilelang.PassConfigKey.TL_DISABLE_FAST_MATH] = True
elif hasattr(tilelang.PassConfigKey, "TL_ENABLE_FAST_MATH"):
pass_configs[tilelang.PassConfigKey.TL_ENABLE_FAST_MATH] = False
_is_hip = is_hip()
_is_gfx95_supported = is_gfx95_supported()
_is_fp8_fnuz = is_fp8_fnuz()
BF16 = "bfloat16"
FP8 = "float8_e4m3fnuz" if _is_fp8_fnuz else "float8_e4m3"
FP32 = "float32"
def fast_log2_ceil(x):
@@ -42,8 +49,8 @@ def act_quant_kernel(
N, in_dtype=BF16, out_dtype=FP8, scale_dtype=FP32, round_scale=False
):
M = T.symbolic("M")
fp8_min = -448.0
fp8_max = 448.0
fp8_min = -224.0 if _is_fp8_fnuz else -448.0
fp8_max = 224.0 if _is_fp8_fnuz else 448.0
fp8_max_inv = 1 / fp8_max
num_stages = 0 if round_scale else 2
blk_m = 32
@@ -108,6 +115,9 @@ def act_quant(
x.size(-1) % block_size == 0
), f"Last dimension size must be divisible by block_size (block_size={block_size})"
N = x.size(-1)
if _is_fp8_fnuz:
y = torch.empty_like(x, dtype=torch.float8_e4m3fnuz)
else:
y = torch.empty_like(x, dtype=torch.float8_e4m3fn)
s = x.new_empty(*x.size()[:-1], N // block_size, dtype=torch.float32)
kernel = act_quant_kernel(N, round_scale=scale_fmt is not None)
@@ -777,9 +787,21 @@ def tilelang_sparse_fwd(
topk = indices.shape[-1]
assert topk == 2048
if _is_hip:
if _is_gfx95_supported:
kernel = sparse_attention_fwd_kernel_v1(
num_heads, d_v, tail_dim, topk, sm_scale=sm_scale, num_stages=1
)
else: # reduce LDS usage on gfx942 target
kernel = sparse_attention_fwd_kernel_v1(
num_heads,
d_v,
tail_dim,
topk,
sm_scale=sm_scale,
block_I=32,
num_stages=1,
threads=128,
)
else:
kernel = sparse_attention_fwd_kernel_v2(
num_heads, d_v, tail_dim, topk, sm_scale=sm_scale