submission 519895
josusanmartin · python · License unknown
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Vendorable · source mirrored · license unknownView source →
No package. Vendor the mirrored source: 43 lines, June 9 Researcher Reciprocity License v1.0.
submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-amd-moe-mxfp4-519895?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 digestsha256:15ca7d9b04adc58da8bc0549dcbce1cd63c96119f6282faeec79ef434c060414
license declaredunknown
license concludedunknown
authorsjosusanmartin
imported2026-08-15
Kernel source
submission.py43 lines
import torch
from aiter import ActivationType, QuantType
from aiter.fused_moe import fused_moe
from task import input_t, output_t
def custom_kernel(data: input_t) -> output_t:
(
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,
)
scrolls · 43 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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