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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 9 new columns ({'technical_repetitions_paired', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p95', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p99', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_median', 'cuda_device_graph_over_cuda_host_graph_wall_ratio_of_medians', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p95', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_median', 'cuda_host_launch_over_cuda_host_graph_wall_ratio_of_medians', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p99'}) and 13 missing columns ({'device_ns_p95', 'status_ok_rows', 'technical_repetitions', 'checksum_equal_rows', 'mechanism', 'wall_ns_p99', 'wall_ns_p95', 'device_ns_p99', 'device_ns_rows', 'device_time_scope', 'device_ns_median', 'wall_ns_median', 'field_exact_rows'}).

This happened while the csv dataset builder was generating data using

hf://datasets/josefchen/ready-cohorts/native/contrasts.csv (at revision 41ff8d06578d4ec68934040a8fb925d3c8b01767), ['hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/native/cell-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/native/contrasts.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/paper/claim-evidence-map.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/resident/cell-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/resident/contrasts.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/source/session-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/trace/cell-seed-evaluations.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/trace/summary.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              placement_id: string
              provider: string
              requested_gpu: string
              device_name: string
              device_uuid: string
              source_file: string
              source_sha256: string
              agents: int64
              steps: int64
              analysis_unit: string
              technical_repetitions_paired: int64
              cuda_device_graph_over_cuda_host_graph_wall_ratio_of_medians: double
              cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_median: double
              cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p95: double
              cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p99: double
              cuda_host_launch_over_cuda_host_graph_wall_ratio_of_medians: double
              cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_median: double
              cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p95: double
              cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p99: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3403
              to
              {'placement_id': Value('string'), 'provider': Value('string'), 'requested_gpu': Value('string'), 'device_name': Value('string'), 'device_uuid': Value('string'), 'source_file': Value('string'), 'source_sha256': Value('string'), 'agents': Value('int64'), 'steps': Value('int64'), 'mechanism': Value('string'), 'analysis_unit': Value('string'), 'technical_repetitions': Value('int64'), 'status_ok_rows': Value('int64'), 'field_exact_rows': Value('int64'), 'checksum_equal_rows': Value('int64'), 'wall_ns_median': Value('float64'), 'wall_ns_p95': Value('float64'), 'wall_ns_p99': Value('float64'), 'device_time_scope': Value('string'), 'device_ns_rows': Value('int64'), 'device_ns_median': Value('float64'), 'device_ns_p95': Value('float64'), 'device_ns_p99': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 9 new columns ({'technical_repetitions_paired', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p95', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p99', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_median', 'cuda_device_graph_over_cuda_host_graph_wall_ratio_of_medians', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_p95', 'cuda_device_graph_over_cuda_host_graph_paired_wall_ratio_median', 'cuda_host_launch_over_cuda_host_graph_wall_ratio_of_medians', 'cuda_host_launch_over_cuda_host_graph_paired_wall_ratio_p99'}) and 13 missing columns ({'device_ns_p95', 'status_ok_rows', 'technical_repetitions', 'checksum_equal_rows', 'mechanism', 'wall_ns_p99', 'wall_ns_p95', 'device_ns_p99', 'device_ns_rows', 'device_time_scope', 'device_ns_median', 'wall_ns_median', 'field_exact_rows'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/josefchen/ready-cohorts/native/contrasts.csv (at revision 41ff8d06578d4ec68934040a8fb925d3c8b01767), ['hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/native/cell-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/native/contrasts.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/paper/claim-evidence-map.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/resident/cell-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/resident/contrasts.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/source/session-summary.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/trace/cell-seed-evaluations.csv', 'hf://datasets/josefchen/ready-cohorts@41ff8d06578d4ec68934040a8fb925d3c8b01767/trace/summary.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

placement_id
string
provider
string
requested_gpu
string
device_name
string
device_uuid
string
source_file
string
source_sha256
string
agents
int64
steps
int64
mechanism
string
analysis_unit
string
technical_repetitions
int64
status_ok_rows
int64
field_exact_rows
int64
checksum_equal_rows
int64
wall_ns_median
float64
wall_ns_p95
float64
wall_ns_p99
float64
device_time_scope
string
device_ns_rows
int64
device_ns_median
float64
device_ns_p95
float64
device_ns_p99
float64
native-dispatch-001-lambda-h100-p1
lambda
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NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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native-dispatch-001-lambda-h100-p1
lambda
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NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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native-dispatch-001-lambda-h100-p1
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NVIDIA H100 80GB HBM3
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data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_host_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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cuda_host_launch
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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cuda_device_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_host_graph
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native-dispatch-001-lambda-h100-p1
lambda
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NVIDIA H100 80GB HBM3
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cpu_cpp
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_device_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_host_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_host_launch
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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cpu_cpp
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_device_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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cuda_host_graph
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cpu_cpp
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50
50
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null
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null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
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cuda_device_graph
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50
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complete_parent_and_child_execution_environment
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
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cuda_host_graph
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50
50
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transition_kernels
50
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native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
256
8
cuda_host_launch
placement
50
50
50
50
26,667.5
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33,220.36
transition_kernels
50
21,712
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28,295.04
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
256
64
cpu_cpp
placement
50
50
50
50
77,712
82,949.75
83,635.56
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
256
64
cuda_device_graph
placement
50
50
50
50
79,419.5
80,179.75
80,387.6
complete_parent_and_child_execution_environment
50
74,336
75,185.6
75,200
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
256
64
cuda_host_graph
placement
50
50
50
50
72,067.5
72,385.55
74,638.77
transition_kernels
50
66,464
66,673.6
69,265.92
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
256
64
cuda_host_launch
placement
50
50
50
50
160,984
171,752
174,655.79
transition_kernels
50
156,032
166,726.4
169,701.44
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
1
cpu_cpp
placement
50
50
50
50
8,670
8,701.1
8,713.61
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
1
cuda_device_graph
placement
50
50
50
50
16,494
17,333.05
23,096.47
complete_parent_and_child_execution_environment
50
11,568
12,344
13,117.12
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
1
cuda_host_graph
placement
50
50
50
50
9,316.5
9,607.55
9,650.89
transition_kernels
50
3,760
3,968
4,000.64
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
1
cuda_host_launch
placement
50
50
50
50
9,979
10,532.6
15,958.42
transition_kernels
50
5,008
5,612.8
10,939.52
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
8
cpu_cpp
placement
50
50
50
50
75,529
78,715.9
81,037.83
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
8
cuda_device_graph
placement
50
50
50
50
24,201
24,992.6
25,802.18
complete_parent_and_child_execution_environment
50
19,200
20,003.2
20,160.64
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
8
cuda_host_graph
placement
50
50
50
50
16,868.5
17,067.25
17,167.18
transition_kernels
50
11,296
11,520
11,664.32
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
8
cuda_host_launch
placement
50
50
50
50
27,168
32,328.8
35,436.55
transition_kernels
50
22,256
27,112
30,537.92
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
64
cpu_cpp
placement
50
50
50
50
625,035
631,964.35
632,428.89
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
64
cuda_device_graph
placement
50
50
50
50
83,643
84,719.1
85,225.37
complete_parent_and_child_execution_environment
50
78,592
79,601.6
79,936.64
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
64
cuda_host_graph
placement
50
50
50
50
75,884
76,568
79,040.35
transition_kernels
50
70,784
71,043.2
71,088.32
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
2,048
64
cuda_host_launch
placement
50
50
50
50
164,041.5
173,596.7
181,302.24
transition_kernels
50
159,056
168,593.6
176,295.68
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
1
cpu_cpp
placement
50
50
50
50
68,827
75,610.95
78,253.51
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
1
cuda_device_graph
placement
50
50
50
50
16,751.5
17,344.65
17,699.34
complete_parent_and_child_execution_environment
50
11,808
12,401.6
12,771.84
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
1
cuda_host_graph
placement
50
50
50
50
8,979.5
9,419.35
10,741.44
transition_kernels
50
3,952
4,241.6
4,384
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
1
cuda_host_launch
placement
50
50
50
50
10,533.5
10,925.25
10,987.52
transition_kernels
50
5,520
5,937.6
6,064.96
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
8
cpu_cpp
placement
50
50
50
50
610,964
625,975.4
635,107.47
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
8
cuda_device_graph
placement
50
50
50
50
25,912.5
26,864.3
33,641.74
complete_parent_and_child_execution_environment
50
20,944
21,955.2
28,677.44
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
8
cuda_host_graph
placement
50
50
50
50
17,517
18,232.5
19,063.84
transition_kernels
50
12,544
13,158.4
14,045.76
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
8
cuda_host_launch
placement
50
50
50
50
27,979
31,795.5
34,260.79
transition_kernels
50
22,960
24,542.4
28,837.12
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
64
cpu_cpp
placement
50
50
50
50
5,011,056
5,038,903.35
5,044,558.81
null
0
null
null
null
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
64
cuda_device_graph
placement
50
50
50
50
90,648.5
91,925.35
92,858.15
complete_parent_and_child_execution_environment
50
85,696
86,880
87,933.76
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
64
cuda_host_graph
placement
50
50
50
50
83,042.5
83,868
86,563.66
transition_kernels
50
78,080
78,819.2
78,992.96
native-dispatch-001-lambda-h100-p1
lambda
H100 (80 GB SXM5)
NVIDIA H100 80GB HBM3
7964af6ebe675c48d8719797603d3893
data/raw/native-dispatch-001-lambda-h100-p1-20260811T210728Z-p2682.csv
2ec4c6246c6c6287f443c749ebe6385ee9690a9a4eed00a9119cb96aad024395
16,384
64
cuda_host_launch
placement
50
50
50
50
164,254
174,003.6
177,913.34
transition_kernels
50
159,312
169,044.8
172,930.24
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
1
cpu_cpp
placement
50
50
50
50
158
176
180.55
null
0
null
null
null
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
1
cuda_device_graph
placement
50
50
50
50
11,554
12,056.05
12,793.58
complete_parent_and_child_execution_environment
50
8,800
9,571.2
10,056.32
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
1
cuda_host_graph
placement
50
50
50
50
5,793.5
6,131.4
6,253.47
transition_kernels
50
3,248
3,936
4,048.96
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
1
cuda_host_launch
placement
50
50
50
50
6,347.5
6,650.75
8,008.15
transition_kernels
50
3,888
4,195.2
5,424
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
8
cpu_cpp
placement
50
50
50
50
1,136
1,162.95
1,179.08
null
0
null
null
null
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
8
cuda_device_graph
placement
50
50
50
50
20,462
20,703
21,718.47
complete_parent_and_child_execution_environment
50
17,808
18,353.6
19,345.92
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
8
cuda_host_graph
placement
50
50
50
50
13,274.5
13,671.2
13,766.14
transition_kernels
50
10,624
11,537.6
11,600.32
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
8
cuda_host_launch
placement
50
50
50
50
17,814.5
18,114.15
18,226.75
transition_kernels
50
15,168
16,017.05
16,047.32
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
64
cpu_cpp
placement
50
50
50
50
9,041.5
9,084.55
10,572.65
null
0
null
null
null
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
64
cuda_device_graph
placement
50
50
50
50
102,460.5
102,859.45
102,908.5
complete_parent_and_child_execution_environment
50
99,840
100,177.6
100,272.96
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
64
cuda_host_graph
placement
50
50
50
50
84,536
84,916.8
85,096.85
transition_kernels
50
81,920
82,659.2
82,880.64
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
32
64
cuda_host_launch
placement
50
50
50
50
109,717
111,012.05
115,587.24
transition_kernels
50
107,008
108,454.4
113,358.4
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
256
1
cpu_cpp
placement
50
50
50
50
1,047
1,060.55
1,066
null
0
null
null
null
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
50798f9011b9a145d0237e476534cf0c
data/raw/native-dispatch-001-local-20260811T205817Z-p3867952.csv
a5c1f4a349075b6e76116c4f52163b488ccdae32a7bf66e95fed752e363d3ac6
256
1
cuda_device_graph
placement
50
50
50
50
11,577.5
11,931.55
12,105.65
complete_parent_and_child_execution_environment
50
8,640
9,588.8
9,777.6
native-dispatch-001-local
local
GTX 1660 Ti
NVIDIA GeForce GTX 1660 Ti
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End of preview.

Ready Cohorts: processed evidence

This is the public processed-evidence mirror for Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control by Josef Chen, Independent Researcher.

The input trace bytes are pinned to dataset revision 70036b93a04e61b0ea2706a68b962f4f26774587 and Parquet conversion revision f7c94012d0bfbf66fe4d6ed627699508bbb555ff. This mirror does not redistribute prompt text, tool arguments, tool results, API keys, or provider receipts.

Contents

  • source/: source provenance, session summaries, and derived span features.
  • trace/: the 540 cell-seed evaluations and summary surface for exact equal-relative-deadline packing.
  • resident/: four-placement summaries and paired mechanism contrasts for the device-resident decision study.
  • native/: five-placement summaries and paired contrasts for the fixed nested device-launch negative control.
  • paper/: the release PDF, paper-data manifest, and claim-evidence map.
  • figures/: the three data figures used by the paper.
  • MANIFEST.json: source and public SHA-256 values for every mirrored file.

The resident and native timing rows are technical repetitions. Placement is the outer performance unit. The trace replay is conditional on one 851-session panel, one arrival model, and nine generated swarms. These files do not support hardware-population significance or an end-to-end agent-speedup claim.

Headline cells

At the prospectively frozen trace condition with 100,000 target active sessions, K=256, and a 50 ms launch deadline, the fixed-window share is 30.19%, the exact offline share is 43.00%, and the local upper bound is 45.85%. In the separate mechanism study, the device-resident path is faster than the matched host-round-trip path in all 36 named-placement cells; within-placement row-median ratios range from 1.19x to 2.39x.

Citation

@misc{chen2026readycohortsboundinggpu,
  title         = {Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control},
  author        = {Josef Liyanjun Chen},
  year          = {2026},
  eprint        = {2608.12123},
  archivePrefix = {arXiv},
  primaryClass  = {cs.DC},
  doi           = {10.48550/arXiv.2608.12123},
  url           = {https://arxiv.org/abs/2608.12123}
}

No additional license is asserted by this mirror; upstream source data remain subject to their source repository terms.

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