NCCL#

This workload (test_template_name is NcclTest) allows users to execute NCCL benchmarks within the CloudAI framework.

Usage Example#

Test TOML example:

name = "my_nccl_test"
description = "Example NCCL test"
test_template_name = "NcclTest"

[cmd_args]
docker_image_url = "nvcr.io#nvidia/pytorch:25.06-py3"

Test Scenario example:

name = "nccl-test"

[[Tests]]
id = "nccl.1"
num_nodes = 1
time_limit = "00:05:00"

test_name = "my_nccl_test"

Test-in-Scenario example:

name = "nccl-test"

[[Tests]]
id = "nccl.1"
num_nodes = 1
time_limit = "00:05:00"

name = "my_nccl_test"
description = "Example NCCL test"
test_template_name = "NcclTest"

  [Tests.cmd_args]
  docker_image_url = "nvcr.io#nvidia/pytorch:25.06-py3"
  subtest_name = "all_reduce_perf_mpi"
  iters = 100

API Documentation#

Command Arguments#

class cloudai.workloads.nccl_test.nccl.NCCLCmdArgs(

*,

docker_image_url: str,

subtest_name: Literal['all_reduce_perf_mpi', 'all_gather_perf_mpi', 'alltoall_perf_mpi', 'alltoallv_perf_mpi', 'broadcast_perf_mpi', 'gather_perf_mpi', 'hypercube_perf_mpi', 'reduce_perf_mpi', 'reduce_scatter_perf_mpi', 'scatter_perf_mpi', 'sendrecv_perf_mpi', 'bisection_perf_mpi', 'all_reduce_perf', 'all_gather_perf', 'alltoall_perf', 'alltoallv_perf', 'broadcast_perf', 'gather_perf', 'hypercube_perf', 'reduce_perf', 'reduce_scatter_perf', 'scatter_perf', 'sendrecv_perf', 'bisection_perf'] | list[Literal['all_reduce_perf_mpi', 'all_gather_perf_mpi', 'alltoall_perf_mpi', 'alltoallv_perf_mpi', 'broadcast_perf_mpi', 'gather_perf_mpi', 'hypercube_perf_mpi', 'reduce_perf_mpi', 'reduce_scatter_perf_mpi', 'scatter_perf_mpi', 'sendrecv_perf_mpi', 'bisection_perf_mpi', 'all_reduce_perf', 'all_gather_perf', 'alltoall_perf', 'alltoallv_perf', 'broadcast_perf', 'gather_perf', 'hypercube_perf', 'reduce_perf', 'reduce_scatter_perf', 'scatter_perf', 'sendrecv_perf', 'bisection_perf']] = 'all_reduce_perf_mpi',

nthreads: int | list[int] = 1,

ngpus: int | list[int] = 1,

minbytes: str | list[str] = '32M',

maxbytes: str | list[str] = '32M',

stepbytes: str | list[str] = '1M',

op: Literal['sum', 'prod', 'min', 'max', 'avg', 'all'] | list[Literal['sum', 'prod', 'min', 'max', 'avg', 'all']] = 'sum',

datatype: Literal['uint8', 'float'] | list[Literal['uint8', 'float']] = 'float',

root: int | list[int] = 0,

iters: int | list[int] = 20,

warmup_iters: int | list[int] = 5,

agg_iters: int | list[int] = 1,

average: int | list[int] = 1,

parallel_init: int | list[int] = 0,

check: int | list[int] = 1,

blocking: int | list[int] = 0,

cudagraph: int | list[int] = 0,

stepfactor: int | list[int] | None = None,

use_deepep_matrix: bool = False,

alltoallv_matrix_container_path: str = '/tmp/traffic_matrix.txt',

**extra_data: Any,

)[source]#

Bases: CmdArgs

NCCL test command arguments.

Test Definition#

class cloudai.workloads.nccl_test.nccl.NCCLTestDefinition(*, name: str, description: str, test_template_name: str, cmd_args: ~cloudai.workloads.nccl_test.nccl.NCCLCmdArgs, dse_excluded_args: list[str] = <factory>, extra_env_vars: dict[str, str | ~typing.List[str]] = {}, extra_cmd_args: dict[str, str] = {}, extra_container_mounts: list[str] = [], git_repos: list[~cloudai._core.installables.git_repo.GitRepo] = [], nsys: ~cloudai.models.workload.NsysConfiguration | None = None, predictor: ~cloudai.models.workload.PredictorConfig | None = None, agent: str = 'grid_search', agent_steps: int = 1, agent_metrics: list[str] = ['default'], agent_reward_function: str = 'inverse', agent_config: dict[str, ~typing.Any] | None = None)[source]#

Bases: TestDefinition

Test object for NCCL.

is_dse_excluded_arg(path: str) → bool#: Return whether a dot-separated cmd_args path should be ignored by DSE.