Arvados CWL Extensions

Arvados provides several extensions to CWL for workflow optimization, site-specific configuration, and to enable access the Arvados API.

To use Arvados CWL extensions, add the following $namespaces section at the top of your CWL file:

$namespaces:
  arv: "http://arvados.org/cwl#"
  cwltool: "http://commonwl.org/cwltool#"

For portability, most Arvados extensions should go into the hints section of your CWL file. This makes it possible for your workflows to run other CWL runners that do not recognize Arvados hints. The difference between hints and requirements is that hints are optional features that can be ignored by other runners and still produce the same output, whereas requirements will fail the workflow if they cannot be fulfilled. For example, arv:IntermediateOutput should go in hints as it will have no effect on non-Arvados platforms, however if your workflow explicitly accesses the Arvados API and will fail without it, you should put arv:APIRequirement in requirements.

• RunInSingleContainer
• SeparateRunner
• RuntimeConstraints
• PartitionRequirement
• APIRequirement
• IntermediateOutput
• Secrets
• WorkflowRunnerResources
• ClusterTarget
• OutputStorageClass
• ProcessProperties
• OutputCollectionProperties
• CUDARequirement
• UsePreemptible
• PreemptionBehavior
• OutOfMemoryRetry

hints:
  arv:RunInSingleContainer: {}

  arv:SeparateRunner:
    runnerProcessName: $(inputs.sample_id)

  arv:RuntimeConstraints:
    keep_cache: 123456
    outputDirType: keep_output_dir

  arv:PartitionRequirement:
    partition: dev_partition

  arv:APIRequirement: {}

  arv:IntermediateOutput:
    outputTTL: 3600

  cwltool:Secrets:
    secrets: [input1, input2]

  arv:WorkflowRunnerResources:
    ramMin: 2048
    coresMin: 2
    keep_cache: 512

  arv:ClusterTarget:
    cluster_id: clsr1
    project_uuid: clsr1-j7d0g-qxc4jcji7n4lafx

  arv:OutputStorageClass:
    intermediateStorageClass: fast_storage
    finalStorageClass: robust_storage

  arv:ProcessProperties:
    processProperties:
      property1: value1
      property2: $(inputs.value2)

  arv:OutputCollectionProperties:
    outputProperties:
      property1: value1
      property2: $(inputs.value2)

  cwltool:CUDARequirement:
    cudaVersionMin: "11.0"
    cudaComputeCapability: "9.0"
    cudaDeviceCountMin: 1
    cudaDeviceCountMax: 1

  arv:UsePreemptible:
    usePreemptible: true

  arv:PreemptionBehavior:
    resubmitNonPreemptible: true

  arv:OutOfMemoryRetry:
    memoryRetryMultiplier: 2
    memoryErrorRegex: "custom memory error"

arv:RunInSingleContainer

Apply this to a workflow step that runs a subworkflow. Indicates that all the steps of the subworkflow should run together in a single container and not be scheduled separately. If you have a sequence of short-running steps (less than 1-2 minutes each) this enables you to avoid scheduling and data transfer overhead by running all the steps together at once. To use this feature, cwltool must be installed in the container image.

arv:SeparateRunner

Apply this to a workflow step that runs a subworkflow. Indicates that Arvados should launch a new workflow runner to manage that specific subworkflow instance. If used on a scatter step, each scatter item is launched separately. Using this option has three benefits:

• Better organization in the “Subprocesses” table of the main workflow, including the ability to provide a custom name for the step
• When re-running a batch that has run before, an entire subworkflow may be reused as a unit, which is faster than determining reuse for each step.
• Significantly faster submit rate compared to invoking arvados-cwl-runner to launch individual workflow instances separately.

The disadvantage of this option is that because it does launch an additional workflow runner, that workflow runner consumes more compute resources compared to having all the steps managed by a single runner.

arv:RuntimeConstraints

Set Arvados-specific runtime hints.

local_output_dir: Use regular file system local to the compute node. There must be sufficient local scratch space to store entire output; specify this with outdirMin of ResourceRequirement. Files are batch uploaded to Keep when the process completes. Most compatible, but upload step can be time consuming for very large files.

keep_output_dir: Use writable Keep mount. Files are streamed to Keep as they are written. Does not consume local scratch space, but does consume RAM for output buffers (up to 192 MiB per file simultaneously open for writing.) Best suited to processes which produce sequential output of large files (non-sequential writes may produced fragmented file manifests). Supports regular files and directories, does not support special files such as symlinks, hard links, named pipes, named sockets, or device nodes.|

arv:PartitionRequirement

Select preferred compute partitions on which to run jobs.

arv:APIRequirement

For CWL v1.1 scripts, if a step requires network access but not specifically access to the Arvados API server, prefer the standard feature NetworkAccess . In the future, these may be differentiated by whether ARVADOS_API_HOST and ARVADOS_API_TOKEN is injected into the container or not.

Indicates that process wants to access to the Arvados API. Will be granted network access and have ARVADOS_API_HOST and ARVADOS_API_TOKEN set in the environment. Tools which rely on the Arvados API being present should put arv:APIRequirement in the requirements section of the tool (rather than hints) to indicate that that it is not portable to non-Arvados CWL runners.

Use arv:APIRequirement in hints to enable general (non-Arvados-specific) network access for a tool.

arv:IntermediateOutput

Specify desired handling of intermediate output collections.

cwltool:Secrets

Indicate that one or more input parameters are “secret”. Must be applied at the top level Workflow. Secret parameters are not stored in keep, are hidden from logs and API responses, and are wiped from the database after the workflow completes.

Note: currently, workflows with secrets must be submitted on the command line using arvados-cwl-runner. Workflows with secrets submitted through Workbench will not properly obscure the secret inputs.

arv:WorkflowRunnerResources

Specify resource requirements for the workflow runner process (arvados-cwl-runner) that manages a workflow run. Must be applied to the top level workflow. Will also be set implicitly when using --submit-runner-ram on the command line along with --create-workflow or --update-workflow. Use this to adjust the runner’s allocation if the workflow runner is getting “out of memory” exceptions or being killed by the out-of-memory (OOM) killer.

arv:ClusterTarget

Specify which Arvados cluster should execute a container or subworkflow, and the parent project for the container request.

arv:OutputStorageClass

Specify the storage class to use for intermediate and final outputs.

arv:ProcessProperties

Specify extra properties that will be set on container requests created by the workflow. May be set on a Workflow or a CommandLineTool. Setting custom properties on a container request simplifies queries to find the workflow run later on.

arv:OutputCollectionProperties

Specify custom properties that will be set on the output collection of the workflow step.

cwltool:CUDARequirement

Request support for Nvidia CUDA GPU acceleration in the container. Assumes that the CUDA runtime (SDK) is installed in the container, and the host will inject the CUDA driver libraries into the container (equal or later to the version requested).

arv:UsePreemptible

Specify whether a workflow step should request preemptible (e.g. AWS Spot market) instances. Such instances are generally cheaper, but can be taken back by the cloud provider at any time (preempted) causing the step to fail. When this happens, Arvados will automatically re-try the step, up to the configuration value of Containers.MaxRetryAttempts (default 3) times.

arv:PreemptionBehavior

This option determines the behavior when arvados-cwl-runner detects that a workflow step was cancelled because the preemptible (spot market) instance it was running on was reclaimed by the cloud provider. If ‘true’, instead of the retry behavior described above in ‘UsePreemptible’, on the first failure the workflow step will be re-submitted with preemption disabled, so it will be scheduled to run on non-preemptible (on-demand) instances.

When preemptible instances are reclaimed, this is a signal that the cloud provider has restricted capacity for low priority preemptible instance. As a result, the default behavior of turning around and rescheduling or launching on another preemptible instance has higher risk of being preempted a second or third time, spending more time and money but making no progress. This option provides an alternate fallback behavior, by attempting to run the step on a preemptible instance the first time (saving money), but re-running the step as non-preemptible if the first attempt was preempted (ensuring continued progress).

This behavior applied to each step individually. If a step is preempted, then successfully re-run as non-preemptible, it does not affect the behavior of the next step, which will first be launched as preemptible, and so forth.

arv:OutOfMemoryRetry

Specify that when a workflow step appears to have failed because it did not request enough RAM, it should be re-submitted with more RAM. Out of memory conditions are detected either by the container being unexpectedly killed (exit code 137) or by matching a pattern in the container’s output (see memoryErrorRegex). Retrying will increase the base RAM request by the value of memoryRetryMultiplier. For example, if the original RAM request was 10 GiB and the multiplier is 1.5, then it will re-submit with 15 GiB.

Containers are only re-submitted once. If it fails a second time after increasing RAM, then the worklow step will still fail.

Also note that expressions that use $(runtime.ram) (such as dynamic command line parameters) are not reevaluated when the container is resubmitted.

arv:dockerCollectionPDH

This is an optional extension field appearing on the standard DockerRequirement. It specifies the portable data hash of the Arvados collection containing the Docker image. If present, it takes precedence over dockerPull or dockerImageId.

requirements:
  DockerRequirement:
    dockerPull: "debian:10"
    arv:dockerCollectionPDH: "feaf1fc916103d7cdab6489e1f8c3a2b+174"

Deprecated extensions

The following extensions are deprecated because equivalent features are part of the CWL v1.1 standard.

hints:
  cwltool:LoadListingRequirement:
    loadListing: shallow_listing
  arv:ReuseRequirement:
    enableReuse: false
  cwltool:TimeLimit:
    timelimit: 14400

cwltool:LoadListingRequirement

For CWL v1.1 scripts, this is deprecated in favor of loadListing or LoadListingRequirement

In CWL v1.0 documents, the default behavior for Directory objects is to recursively expand the listing for access by parameter references an expressions. For directory trees containing many files, this can be expensive in both time and memory usage. Use cwltool:LoadListingRequirement to change the behavior for expansion of directory listings in the workflow runner.

no_listing: Do not expand directory listing at all. The listing field on the Directory object will be undefined.

shallow_listing: Only expand the first level of directory listing. The listing field on the toplevel Directory object will contain the directory contents, however listing will not be defined on subdirectories.

deep_listing: Recursively expand all levels of directory listing. The listing field will be provided on the toplevel object and all subdirectories.

arv:ReuseRequirement

For CWL v1.1 scripts, this is deprecated in favor of WorkReuse .

Enable/disable work reuse for current process. Default true (work reuse enabled).

cwltool:TimeLimit

For CWL v1.1 scripts, this is deprecated in favor of ToolTimeLimit

Set an upper limit on the execution time of a CommandLineTool or ExpressionTool. A tool execution which exceeds the time limit may be preemptively terminated and considered failed. May also be used by batch systems to make scheduling decisions.