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submission 703446

rt11 · python · License unknown

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Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 117 lines, June 9 Researcher Reciprocity License v1.0.

submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-amd-mxfp4-mm-703446?include=source"
interfacepython
Compatibility
measured onAMD Instinct MI355X
declared hardwareAMD Instinct MI355X
architecturesgfx950
dtypesbf16, mxfp4

Benchmark evidence

1 measurement across 1 GPU, fastest first.

Operation / workload
Hardware
Latency
Rank
Observed
AMD MXFP4 GEMMsuite of 6 cases
AMD Instinct MI355X
8.90µs
#97 of 1143
2026-04-02

Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:2b0e1f8a805425ac34279562f1d82002011330acfe4f8dbd5d44e5262240de94
license declaredunknown
license concludedunknown
authorsrt11
imported2026-08-15

Kernel source

submission.py117 lines
# Generated by pack.py; edit src_cfg1.py..src_cfg6.py, then rerun pack.py.
from __future__ import annotations

import base64
import gzip
import linecache

from task import input_t, output_t


CFG1_SHAPE = (4, 2880, 512)
CFG2_SHAPE = (16, 2112, 7168)
CFG3_SHAPE = (32, 4096, 512)
CFG4_SHAPE = (32, 2880, 512)
CFG5_SHAPE = (64, 7168, 2048)
CFG6_SHAPE = (256, 3072, 1536)

# BEGIN SRC_CFG1_B64
SRC_CFG1_B64 = """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"""
# END SRC_CFG1_B64

# BEGIN SRC_CFG2_B64
SRC_CFG2_B64 = """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"""
# END SRC_CFG2_B64

# BEGIN SRC_CFG3_B64
SRC_CFG3_B64 = """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"""
# END SRC_CFG3_B64

# BEGIN SRC_CFG4_B64
SRC_CFG4_B64 = """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"""
# END SRC_CFG4_B64

# BEGIN SRC_CFG5_B64
SRC_CFG5_B64 = """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"""
# END SRC_CFG5_B64

# BEGIN SRC_CFG6_B64
SRC_CFG6_B64 = """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"""
# END SRC_CFG6_B64

CFG_BLOBS = {
    CFG1_SHAPE: SRC_CFG1_B64,
    CFG2_SHAPE: SRC_CFG2_B64,
    CFG3_SHAPE: SRC_CFG3_B64,
    CFG4_SHAPE: SRC_CFG4_B64,
    CFG5_SHAPE: SRC_CFG5_B64,
    CFG6_SHAPE: SRC_CFG6_B64,
}

CFG_CACHE = {}


def decode_blob(blob: str) -> str:
    return gzip.decompress(base64.b64decode(blob)).decode("utf-8")


def load_cfg_kernel(shape: tuple[int, int, int]):
    kernel = CFG_CACHE.get(shape)
    if kernel is not None:
        return kernel
    module_name = f"_mxfp4_cfg_{shape[0]}_{shape[1]}_{shape[2]}"
    filename = f"{module_name}.py"
    source = decode_blob(CFG_BLOBS[shape])
    linecache.cache[filename] = (
        len(source),
        None,
        source.splitlines(keepends=True),
        filename,
    )
    namespace = {
        "__name__": module_name,
        "__file__": filename,
    }
    exec(compile(source, filename, "exec"), namespace)
    kernel = namespace["custom_kernel"]
    CFG_CACHE[shape] = kernel
    return kernel


def _baseline_quant_mxfp4(x, shuffle=True):
    from aiter import dtypes
    from aiter.ops.triton.quant import dynamic_mxfp4_quant
    from aiter.utility.fp4_utils import e8m0_shuffle

    x_fp4, bs_e8m0 = dynamic_mxfp4_quant(x)
    if shuffle:
        bs_e8m0 = e8m0_shuffle(bs_e8m0)
    return x_fp4.view(dtypes.fp4x2), bs_e8m0.view(dtypes.fp8_e8m0)


def baseline_custom_kernel(data: input_t) -> output_t:
    import aiter
    from aiter import dtypes

    A, B, _, B_shuffle, B_scale_sh = data
    A = A.contiguous()
    B = B.contiguous()

    A_q, A_scale_sh = _baseline_quant_mxfp4(A, shuffle=True)
    return aiter.gemm_a4w4(
        A_q,
        B_shuffle,
        A_scale_sh,
        B_scale_sh,
        dtype=dtypes.bf16,
        bpreshuffle=True,
    )


def custom_kernel(data: input_t) -> output_t:
    a, b, _, _, _ = data
    shape = (a.shape[0], b.shape[0], a.shape[1])
    blob = CFG_BLOBS.get(shape)
    if blob is None:
        return baseline_custom_kernel(data)
    return load_cfg_kernel(shape)(data)
scrolls · 117 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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