submission 754572
ftyghome · python · License unknown
Use it
Vendorable · source mirrored · license unknownView source →
No package. Vendor the mirrored source: 164 lines, June 9 Researcher Reciprocity License v1.0.
submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-amd-moe-mxfp4-754572?include=source"interfacepython
Compatibility
measured onAMD Instinct MI355X
declared hardwareAMD Instinct MI355X
architecturesgfx950
dtypesbf16, fp32, fp8_e8m0, int32, mxfp4
Benchmark evidence
1 measurement across 1 GPU, fastest first.
Operation / workload
Hardware
Latency
Rank
Observed
Reported · How evidence levels are derived →
Source and license
sourceavailable
revision digestsha256:d54d706f90e27b89b8bc81f764c99ec508dc8eb5dbd41ace79773b061fe2de7f
license declaredunknown
license concludedunknown
authorsftyghome
imported2026-08-15
Kernel source
submission.py164 lines
#!POPCORN leaderboard amd-moe-mxfp4
import os
os.environ['PYTORCH_ROCM_ARCH'] = 'gfx950'
# Find best ROCm installation
for _rocm_path in ['/opt/rocm-7.1.1', '/opt/rocm-7.2.0', '/opt/rocm']:
if os.path.isdir(_rocm_path) and os.path.isfile(os.path.join(_rocm_path, 'bin', 'hipcc')):
os.environ['ROCM_HOME'] = _rocm_path
os.environ['ROCM_PATH'] = _rocm_path
os.environ['HIP_PATH'] = _rocm_path
os.environ['PATH'] = os.path.join(_rocm_path, 'bin') + ':' + os.environ.get('PATH', '')
break
import torch
from torch.utils.cpp_extension import load_inline
from task import input_t, output_t
import base64
import bz2
import shutil
import glob as globmod
CPP_WRAPPER = """
void run_from_python(
int bs, int d_hidden, int d_expert,
int d_hidden_pad, int d_expert_pad,
int n_routed_experts, int n_shared_experts,
int n_experts_per_token, int total_top_k,
unsigned long long hidden_states_ptr,
unsigned long long gate_up_weight_shuffled_ptr,
unsigned long long down_weight_shuffled_ptr,
unsigned long long gate_up_weight_scale_shuffled_ptr,
unsigned long long down_weight_scale_shuffled_ptr,
unsigned long long topk_weights_ptr,
unsigned long long topk_ids_ptr,
unsigned long long output_ptr);
"""
CUDA_SRC_COMPRESSED = """
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
"""
CUDA_SRC = bz2.decompress(base64.b64decode(CUDA_SRC_COMPRESSED)).decode('utf-8')
# Force clean build: delete ALL cached torch extensions for this module
MODULE_NAME = 'moe_mxfp4_6179b162'
for cache_root in [
os.path.expanduser('~/.cache/torch_extensions/'),
'/tmp/torch_extensions/',
]:
if os.path.isdir(cache_root):
for d in os.listdir(cache_root):
mod_dir = os.path.join(cache_root, d, MODULE_NAME)
if os.path.isdir(mod_dir):
print(f"Removing cached build: {mod_dir}")
shutil.rmtree(mod_dir)
module = load_inline(
name=MODULE_NAME,
cpp_sources=[CPP_WRAPPER],
cuda_sources=[CUDA_SRC],
functions=['run_from_python'],
verbose=True,
extra_cuda_cflags=[
"--offload-arch=gfx950",
"-std=c++20",
"-O3",
"-fno-fast-math",
"-ffp-contract=fast",
"-U__HIP_NO_HALF_OPERATORS__",
"-U__HIP_NO_HALF_CONVERSIONS__",
],
extra_cflags=["-O3", "-march=native"],
)
_output_buf = None
# AITER fallback for non-benchmark shapes
from aiter import ActivationType, QuantType
from aiter.fused_moe import fused_moe
# Benchmark shapes our custom kernel is validated for
_BENCHMARK_SHAPES = ((7168, 256, 256, 8), (7168, 256, 256, 8), (7168, 256, 256, 8), (7168, 512, 32, 8), (7168, 512, 32, 8), (7168, 512, 32, 8), (7168, 2048, 32, 8))
def _is_benchmark_shape(config):
key = (config["d_hidden"], config["d_expert"],
config["n_routed_experts"], config["n_experts_per_token"])
return key in _BENCHMARK_SHAPES
def _aiter_fallback(data):
(
hidden_states, gate_up_weight, down_weight,
gate_up_weight_scale, down_weight_scale,
gate_up_weight_shuffled, down_weight_shuffled,
gate_up_weight_scale_shuffled, down_weight_scale_shuffled,
topk_weights, topk_ids, config,
) = data
hidden_pad = config["d_hidden_pad"] - config["d_hidden"]
intermediate_pad = config["d_expert_pad"] - config["d_expert"]
return fused_moe(
hidden_states, gate_up_weight_shuffled, down_weight_shuffled,
topk_weights, topk_ids, expert_mask=None,
activation=ActivationType.Silu, quant_type=QuantType.per_1x32,
doweight_stage1=False,
w1_scale=gate_up_weight_scale_shuffled,
w2_scale=down_weight_scale_shuffled,
a1_scale=None, a2_scale=None,
hidden_pad=hidden_pad, intermediate_pad=intermediate_pad,
)
def custom_kernel(data: input_t) -> output_t:
global _output_buf
(
hidden_states,
gate_up_weight,
down_weight,
gate_up_weight_scale,
down_weight_scale,
gate_up_weight_shuffled,
down_weight_shuffled,
gate_up_weight_scale_shuffled,
down_weight_scale_shuffled,
topk_weights,
topk_ids,
config,
) = data
# Fallback to AITER for non-benchmark shapes
if not _is_benchmark_shape(config):
return _aiter_fallback(data)
M = hidden_states.shape[0]
d_hidden = config["d_hidden"]
# Pre-allocate output buffer (reuse across calls with same shape)
if _output_buf is None or _output_buf.shape[0] < M or _output_buf.shape[1] != d_hidden:
_output_buf = torch.empty(M, d_hidden, dtype=torch.bfloat16, device=hidden_states.device)
output = _output_buf[:M]
# All tuning (tile sizes, sort block) is in the C++ dispatch table.
# Python just passes input data — zero heuristic logic here.
module.run_from_python(
config["bs"],
d_hidden,
config["d_expert"],
config["d_hidden_pad"],
config["d_expert_pad"],
config["n_routed_experts"],
config["n_shared_experts"],
config["n_experts_per_token"],
config["total_top_k"],
hidden_states.data_ptr(),
gate_up_weight_shuffled.data_ptr(),
down_weight_shuffled.data_ptr(),
gate_up_weight_scale_shuffled.data_ptr(),
down_weight_scale_shuffled.data_ptr(),
topk_weights.data_ptr(),
topk_ids.data_ptr(),
output.data_ptr(),
)
return output
scrolls · 164 lines total
Source code from GPU Mode and the KernelBot dataset · June 9 Researcher Reciprocity License v1.0
Best evidence level for this revision: reported
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