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submission 632161

Hamza · python · License unknown

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Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 64 lines, June 9 Researcher Reciprocity License v1.0.

submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-amd-moe-mxfp4-632161?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
AMD MXFP4 MoEsuite of 7 cases
AMD Instinct MI355X
156.3µs
#256 of 782
2026-03-25

Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:486926ed858c3648c7947d56e92bc283fdbe3f67a8a4e001a5594345e6a9eacb
license declaredunknown
license concludedunknown
authorsHamza
imported2026-08-15

Kernel source

submission.py64 lines
#!POPCORN leaderboard amd-moe-mxfp4
#!POPCORN gpu MI355X

import os
import torch
from task import input_t, output_t

from aiter import ActivationType, QuantType
from aiter.fused_moe import fused_moe

_PAD_CACHE = {}


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

    M = topk_ids.shape[0]

    # Per-shape kernel backend selection via env vars.
    # get_2stage_cfgs() and get_ksplit() are LRU-cached per shape,
    # so env vars only matter on first (warmup) call.
    if M <= 128:
        # Trigger cktile backend with split_k=2 for decode shapes.
        # BYPASS_TUNE_CONFIG=1 skips CSV kernel selection, forcing
        # the default heuristic path which respects AITER_KSPLIT.
        os.environ["AITER_KSPLIT"] = "2"
        os.environ["AITER_BYPASS_TUNE_CONFIG"] = "1"
    else:
        # Keep CSV-tuned ck2stages for large-M 256-expert shapes,
        # and default ck backend for large-M 32-expert shapes.
        os.environ["AITER_KSPLIT"] = "0"
        os.environ["AITER_BYPASS_TUNE_CONFIG"] = "0"

    cfg_id = id(config)
    cached = _PAD_CACHE.get(cfg_id)
    if cached is not None:
        hidden_pad, intermediate_pad = cached
    else:
        hidden_pad = config["d_hidden_pad"] - config["d_hidden"]
        intermediate_pad = config["d_expert_pad"] - config["d_expert"]
        _PAD_CACHE[cfg_id] = (hidden_pad, intermediate_pad)

    return fused_moe(
        hidden_states, gate_up_weight_shuffled, down_weight_shuffled,
        topk_weights, topk_ids,
        activation=ActivationType.Silu, quant_type=QuantType.per_1x32,
        w1_scale=gate_up_weight_scale_shuffled,
        w2_scale=down_weight_scale_shuffled,
        hidden_pad=hidden_pad, intermediate_pad=intermediate_pad,
    )
scrolls · 64 lines total

Source code from GPU Mode and the KernelBot dataset · June 9 Researcher Reciprocity License v1.0

Changes from previous submission

Against this author's previous submission submission 630031.

⋯ 28 unchanged lines
M = topk_ids.shape[0]
- # For small batch sizes, ksplit=2 triggers the cktile backend
- # which is ~30% faster for 32-expert shapes with M<=128.
- # For large M, the default ck backend is better.
- # get_ksplit() is LRU-cached per shape, so the env var only
- # matters on the first (warmup) call for each unique shape.
+ # Per-shape kernel backend selection via env vars.
+ # get_2stage_cfgs() and get_ksplit() are LRU-cached per shape,
+ # so env vars only matter on first (warmup) call.
if M <= 128:
+ # Trigger cktile backend with split_k=2 for decode shapes.
+ # BYPASS_TUNE_CONFIG=1 skips CSV kernel selection, forcing
+ # the default heuristic path which respects AITER_KSPLIT.
os.environ["AITER_KSPLIT"] = "2"
+ os.environ["AITER_BYPASS_TUNE_CONFIG"] = "1"
else:
+ # Keep CSV-tuned ck2stages for large-M 256-expert shapes,
+ # and default ck backend for large-M 32-expert shapes.
os.environ["AITER_KSPLIT"] = "0"
+ os.environ["AITER_BYPASS_TUNE_CONFIG"] = "0"
cfg_id = id(config)
cached = _PAD_CACHE.get(cfg_id)
scrolls · 26 diff lines total

Best evidence level for this revision: reported

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