wfcommons.wfbench

wfcommons.wfbench.bench

class wfcommons.wfbench.bench.WorkflowBenchmark(recipe: Type[WfChefWorkflowRecipe], num_tasks: int, logger: Logger | None = None, with_flowcept=False)

Bases: object

Generate a workflow benchmark instance based on a workflow recipe (WfChefWorkflowRecipe)

Parameters:

  • recipe (Type[WfChefWorkflowRecipe]) – A workflow recipe.

  • num_tasks (int) – Total number of tasks in the benchmark workflow.

  • logger (Optional[Logger]) – The logger where to log information/warning or errors.

create_benchmark(save_dir: Path, percent_cpu: float | Dict[str, float] = 0.6, cpu_work: int | Dict[str, int] = None, gpu_work: int | Dict[str, int] = None, time: int | None = None, data: int | Dict[str, str] | None = None, mem: float | None = None, lock_files_folder: Path | None = None, regenerate: bool | None = True, rundir: Path | None = None) → Path

Create a workflow benchmark.

Parameters:

  • save_dir (pathlib.Path) – Folder to generate the workflow benchmark JSON instance and input data files.

  • percent_cpu (Union[float, Dict[str, float]]) – The percentage of CPU threads.

  • cpu_work (Union[int, Dict[str, int]]) – CPU work per workflow task.

  • gpu_work (Union[int, Dict[str, int]]) – GPU work per workflow task.

  • time (Optional[int]) – Time limit for running each task (in seconds).

  • data (Optional[Union[int, Dict[str, str]]]) – Dictionary of input size files per workflow task type or total workflow data footprint (in MB).

  • mem (Optional[float]) – Maximum amount of memory consumption per task (in MB).

  • lock_files_folder (Optional[pathlib.Path])

  • regenerate (Optional[bool]) – Whether to regenerate the workflow tasks

  • rundir (Optional[pathlib.Path]) – If you would like for the files to be created/saved in a different directory.

Returns:

The path to the workflow benchmark JSON instance.

Return type:

pathlib.Path

create_benchmark_from_input_file(save_dir: Path, input_file: Path, lock_files_folder: Path | None = None, rundir: Path | None = None) → Path

Create a workflow benchmark.

Parameters:

  • save_dir (pathlib.Path) – Folder to generate the workflow benchmark JSON instance and input data files.

  • input_file (pathlib.Path)

  • lock_files_folder (Optional[pathlib.Path])

  • rundir (Optional[pathlib.Path]) – If you would like for the files to be created/saved in a different directory.

Returns:

The path to the workflow benchmark JSON instance.

Return type:

pathlib.Path

create_benchmark_from_synthetic_workflow(save_dir: Path, workflow: Workflow, percent_cpu: float | Dict[str, float] = 0.6, cpu_work: int | Dict[str, int] = None, gpu_work: int | Dict[str, int] = None, time: int | None = None, mem: float | None = None, lock_files_folder: Path | None = None, rundir: Path | None = None) → Path

Create a workflow benchmark from a synthetic workflow

Parameters:

  • save_dir (pathlib.Path) – Folder to generate the workflow benchmark JSON instance and input data files.

  • workflow (Workflow) – The (synthetic) workflow to use as a benchmark.

  • percent_cpu (Union[float, Dict[str, float]]) – The maximum percentage of CPU threads.

  • cpu_work (Union[int, Dict[str, int]]) – Maximum CPU work per workflow task.

  • gpu_work (Union[int, Dict[str, int]]) – Maximum GPU work per workflow task.

  • time (Optional[int]) – Time limit for running each task (in seconds).

  • mem (Optional[float]) – Maximum amount of memory consumption per task (in MB).

  • lock_files_folder (Optional[pathlib.Path])

  • rundir (Optional[pathlib.Path]) – If you would like for the files to be created/saved in a different directory.

Returns:

The path to the workflow benchmark JSON instance.

Return type:

pathlib.Path

generate_input_file(path: Path) → None

Generates input file where customization of cpu percentage, cpu work, gpu work, data size

Parameters:

path (pathlib.Path)

run(json_path: Path, save_dir: Path) → None

Run the benchmark workflow locally (for test purposes only).

Parameters:

json_path (pathlib.Path)

Param:

save_dir:

wfcommons.wfbench.bench.assigning_correct_files(task: Dict[str, str]) → List[str]
wfcommons.wfbench.bench.clean_entry(entry)
wfcommons.wfbench.bench.cleanup_sys_files() → None

Remove files already used

wfcommons.wfbench.bench.generate_sys_data(num_files: int, tasks: Dict[str, int], save_dir: Path) → None

Generate workflow’s input data

Parameters:

  • num_files (int) – number of each file to be generated.

  • tasks (Dict[str, int]) – Dictionary with the name of the tasks and their data sizes.

  • save_dir (pathlib.Path) – Folder to generate the workflow benchmark’s input data files.

wfcommons.wfbench.translator.nextflow

class wfcommons.wfbench.translator.nextflow.NextflowTranslator(workflow: Workflow | Path, logger: Logger | None = None)

Bases: Translator

A WfFormat parser for creating Nextflow workflow applications.

Parameters:

  • workflow (Union[Workflow, pathlib.Path],) – Workflow benchmark object or path to the workflow benchmark JSON instance.

  • logger (Logger) – The logger where to log information/warning or errors (optional).

translate(output_folder: Path) → None

Translate a workflow benchmark description(WfFormat) into a Nextflow workflow application.

Parameters:

output_folder (pathlib.Path) – The path to the folder in which the workflow benchmark will be generated.

workflow: Workflow

wfcommons.wfbench.translator.pegasus

wfcommons.wfbench.translator.swift_t

wfcommons.wfbench.translator.taskvine