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
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
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
constraints: list<item: string>
  child 0, item: string
tags: list<item: string>
  child 0, item: string
reference: string
op_type: 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 147, 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 127, 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 483, 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 343, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, 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
              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
              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
              constraints: list<item: string>
                child 0, item: string
              tags: list<item: string>
                child 0, item: string
              reference: string
              op_type: 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	10	gemm, conv2d, conv2d_depthwise	`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	124

expected_sets_sve.json: the 85 evaluated definitions (23 ncnn, 26 llama.cpp, 26 SIMD Loops, 10 KleidiAI).
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.

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.

Downloads last month: 2,132

Total file size:

23.1 MB

ARM Bench Trace

Contents

Tasks and baselines

Layout

License