Datasets:

arm-bench
/

arm-bench-trace

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
name: string
definition: string
dataset: string
author: string
description: string
spec: struct<language: string, target_hardware: list<item: string>, entry_point: string, dependencies: lis (... 113 chars omitted)
  child 0, language: string
  child 1, target_hardware: list<item: string>
      child 0, item: string
  child 2, entry_point: string
  child 3, dependencies: list<item: null>
      child 0, item: null
  child 4, isa_features: list<item: string>
      child 0, item: string
  child 5, compile_flags: list<item: string>
      child 0, item: string
  child 6, link_flags: list<item: null>
      child 0, item: null
sources: list<item: struct<path: string, content: string>>
  child 0, item: struct<path: string, content: string>
      child 0, path: string
      child 1, content: string
op_type: string
reference: string
outputs: struct<output: struct<shape: list<item: string>, dtype: string>>
  child 0, output: struct<shape: list<item: string>, dtype: string>
      child 0, shape: list<item: string>
          child 0, item: string
      child 1, dtype: string
tags: list<item: string>
  child 0, item: string
constraints: list<item: string>
  child 0, item: string
axes: struct<H: struct<type: string>, W: struct<type: string>, H_out: struct<type: string>, W_out: struct< (... 218 chars omitted)
  child 0, H: struct<type: string>
      child 0, type: string
  child 1, W: struct<type: string>
      child 0, type: string
  child 2, H_out: struct<type: string>
      child 0, type: string
  child 3, W_out: struct<type: string>
      child 0, type: string
  child 4, N: struct<type: string, value: int64>
      child 0, type: string
      child 1, value: int64
  child 5, C_in: struct<type: string, value: int64>
      child 0, type: string
      child 1, value: int64
  child 6, C_out: struct<type: string, value: int64>
      child 0, type: string
      child 1, value: int64
  child 7, Kh: struct<type: string, value: int64>
      child 0, type: string
      child 1, value: int64
  child 8, Kw: struct<type: string, value: int64>
      child 0, type: string
      child 1, value: int64
inputs: struct<input: struct<shape: list<item: string>, dtype: string>, weight: struct<shape: list<item: str (... 77 chars omitted)
  child 0, input: struct<shape: list<item: string>, dtype: string>
      child 0, shape: list<item: string>
          child 0, item: string
      child 1, dtype: string
  child 1, weight: struct<shape: list<item: string>, dtype: string>
      child 0, shape: list<item: string>
          child 0, item: string
      child 1, dtype: string
  child 2, bias: struct<shape: list<item: string>, dtype: string>
      child 0, shape: list<item: string>
          child 0, item: string
      child 1, dtype: string
to
{'name': Value('string'), 'op_type': Value('string'), 'description': Value('string'), 'tags': List(Value('string')), 'axes': {'H': {'type': Value('string')}, 'W': {'type': Value('string')}, 'H_out': {'type': Value('string')}, 'W_out': {'type': Value('string')}, 'N': {'type': Value('string'), 'value': Value('int64')}, 'C_in': {'type': Value('string'), 'value': Value('int64')}, 'C_out': {'type': Value('string'), 'value': Value('int64')}, 'Kh': {'type': Value('string'), 'value': Value('int64')}, 'Kw': {'type': Value('string'), 'value': Value('int64')}}, 'inputs': {'input': {'shape': List(Value('string')), 'dtype': Value('string')}, 'weight': {'shape': List(Value('string')), 'dtype': Value('string')}, 'bias': {'shape': List(Value('string')), 'dtype': Value('string')}}, 'outputs': {'output': {'shape': List(Value('string')), 'dtype': Value('string')}}, 'constraints': List(Value('string')), 'reference': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              name: string
              definition: string
              dataset: string
              author: string
              description: string
              spec: struct<language: string, target_hardware: list<item: string>, entry_point: string, dependencies: lis (... 113 chars omitted)
                child 0, language: string
                child 1, target_hardware: list<item: string>
                    child 0, item: string
                child 2, entry_point: string
                child 3, dependencies: list<item: null>
                    child 0, item: null
                child 4, isa_features: list<item: string>
                    child 0, item: string
                child 5, compile_flags: list<item: string>
                    child 0, item: string
                child 6, link_flags: list<item: null>
                    child 0, item: null
              sources: list<item: struct<path: string, content: string>>
                child 0, item: struct<path: string, content: string>
                    child 0, path: string
                    child 1, content: string
              op_type: string
              reference: string
              outputs: struct<output: struct<shape: list<item: string>, dtype: string>>
                child 0, output: struct<shape: list<item: string>, dtype: string>
                    child 0, shape: list<item: string>
                        child 0, item: string
                    child 1, dtype: string
              tags: list<item: string>
                child 0, item: string
              constraints: list<item: string>
                child 0, item: string
              axes: struct<H: struct<type: string>, W: struct<type: string>, H_out: struct<type: string>, W_out: struct< (... 218 chars omitted)
                child 0, H: struct<type: string>
                    child 0, type: string
                child 1, W: struct<type: string>
                    child 0, type: string
                child 2, H_out: struct<type: string>
                    child 0, type: string
                child 3, W_out: struct<type: string>
                    child 0, type: string
                child 4, N: struct<type: string, value: int64>
                    child 0, type: string
                    child 1, value: int64
                child 5, C_in: struct<type: string, value: int64>
                    child 0, type: string
                    child 1, value: int64
                child 6, C_out: struct<type: string, value: int64>
                    child 0, type: string
                    child 1, value: int64
                child 7, Kh: struct<type: string, value: int64>
                    child 0, type: string
                    child 1, value: int64
                child 8, Kw: struct<type: string, value: int64>
                    child 0, type: string
                    child 1, value: int64
              inputs: struct<input: struct<shape: list<item: string>, dtype: string>, weight: struct<shape: list<item: str (... 77 chars omitted)
                child 0, input: struct<shape: list<item: string>, dtype: string>
                    child 0, shape: list<item: string>
                        child 0, item: string
                    child 1, dtype: string
                child 1, weight: struct<shape: list<item: string>, dtype: string>
                    child 0, shape: list<item: string>
                        child 0, item: string
                    child 1, dtype: string
                child 2, bias: struct<shape: list<item: string>, dtype: string>
                    child 0, shape: list<item: string>
                        child 0, item: string
                    child 1, dtype: string
              to
              {'name': Value('string'), 'op_type': Value('string'), 'description': Value('string'), 'tags': List(Value('string')), 'axes': {'H': {'type': Value('string')}, 'W': {'type': Value('string')}, 'H_out': {'type': Value('string')}, 'W_out': {'type': Value('string')}, 'N': {'type': Value('string'), 'value': Value('int64')}, 'C_in': {'type': Value('string'), 'value': Value('int64')}, 'C_out': {'type': Value('string'), 'value': Value('int64')}, 'Kh': {'type': Value('string'), 'value': Value('int64')}, 'Kw': {'type': Value('string'), 'value': Value('int64')}}, 'inputs': {'input': {'shape': List(Value('string')), 'dtype': Value('string')}, 'weight': {'shape': List(Value('string')), 'dtype': Value('string')}, 'bias': {'shape': List(Value('string')), 'dtype': Value('string')}}, 'outputs': {'output': {'shape': List(Value('string')), 'dtype': Value('string')}}, 'constraints': List(Value('string')), 'reference': Value('string')}
              because column names don't match

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ARM Bench Trace

Benchmark data for optimizing Arm (AArch64) CPU kernels on three generations of vector extensions: SVE (AWS Graviton3, 256-bit), SVE2 (AWS Graviton4, 128-bit) and SME2 (Apple M4). Each operator definition comes with workloads, a correctness reference and an expert baseline: a candidate kernel is checked against the reference and timed against the baseline.

Source	Definitions	Op types	Expert baseline
ncnn	23	conv2d, conv2d_depthwise, pooling	`baseline-ncnn-arm`
llama.cpp	26	gemm, moe, mha, gqa, mla_decode, mla_prefill, rms_norm	`baseline-llamacpp-arm`
SIMD Loops	47	one loop per definition	`baseline-sve`, `baseline-sve2`, `baseline-sme2`
KleidiAI	30	gemm, conv2d, conv2d_depthwise, softmax	`baseline-kleidiai-arm`
e2e	18	gemm on q4_K / q5_K / q6_K weights of Llama-3.1-8B and Qwen3.5-4B	`baseline-llamacpp-arm`
Total	144

expected_sets_sve.json: the evaluated definitions. ncnn, llama.cpp, simd-loop, kleidiai: the 79 of the main SVE comparison on Graviton3 (23 ncnn, 26 llama.cpp, 24 SIMD Loops, 6 KleidiAI: the KleidiAI kernels with an SVE expert, without softmax_fp32). kleidiai-sme2: the 20 KleidiAI kernels with an SME2 expert, evaluated on M4. loop_120 and loop_124 were removed on 2026-11-10: they sort their input in place, so their timings are not valid (see TASKS.md).
subset_sve.json / subset_sme.json: a 32-definition subset for the SVE and SME2 tiers; they differ only in the KleidiAI GEMM.

Tasks and baselines

TASKS.md lists every definition with its baseline on each tier: whether it runs there and whether it is specialized for that tier. Update it in the same commit whenever you add or remove definitions or baselines, or confirm a baseline on another machine.

Layout

definitions/<op_type>/<name>.json   operator spec: axes, inputs/outputs, PyTorch reference
workloads/<op_type>/<name>.jsonl    one workload per line: var-axis values and how to build each input
solutions/<source>/<author>/...     kernels, with their sources inlined in the JSON
tensors/gemm/<name>/*.npy           recorded activations used by the e2e workloads
runs/e2e-<model>/                   end-to-end measurements for the e2e definitions

The e2e definitions sit with llama.cpp and carry an e2e:<model> tag. Definitions tagged correctness:sqnr (quantized and bf16 kernels) are checked by signal-to-quantization-noise ratio instead of element-wise tolerances.

Solution authors:

baseline-*: the expert baselines (SIMD Loops has one per tier).
reference-scalar, and reference for SIMD Loops: scalar code, the correctness reference.
autovec (SIMD Loops): the loop compiled with the compiler's auto-vectorizer.
Other authors (claude-*, fable-*): kernels written by coding agents, kept as examples; they are not baselines.

Qwen3.5-4B e2e kernels (best of 3)

The coding agent (Claude Code with Claude Fable 5.1) wrote each of the 11 Qwen3.5-4B e2e kernels three times (seeds s1, s2, s3), and we keep the best run of each. The 11 kernels are in solutions/llama.cpp/claude-code-claude-fable-5-1-best-of-3/gemm/; the provenance field of each gives the run it came from, its seed and its score. runs/e2e-qwen3.5-4b/ holds the chosen run of each definition (the agent's trajectory and every code version it wrote), filed under the author of that run, and measurements/ with the end-to-end llama.cpp results (the set is labelled best; gatev2 is the earlier kernel set, measured again for comparison), the KL divergence against stock llama.cpp, the kernel timings against llama.cpp's repacked kernels, and selection.json with all three scores per definition.

The previous Qwen3.5-4B runs are kept unchanged in runs/e2e-qwen3.5-4b-old@2026-09-21/. The Llama-3.1-8B-Instruct kernels and runs are unchanged (claude-code-claude-fable-5-1-gatev2, runs/e2e-llama-3.1-8b/).

Three of the chosen Qwen kernels (q4_K n8192 k2560, q4_K n9216 k2560 and q5_K n8192 k2560) come from a September 22 run whose trajectories were not kept; they have a kernel and a score but no run folder.

License

Released under the Apache-2.0 license. The baselines derive from or wrap ncnn (BSD-3-Clause), llama.cpp / ggml (MIT), KleidiAI (Apache-2.0) and SIMD Loops (BSD-3-Clause); see each project for its license terms.

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Total file size:

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ARM Bench Trace

Contents

Tasks and baselines

Layout

Qwen3.5-4B e2e kernels (best of 3)

License