property1: value1
property2: $(inputs.value2)
- arv:CUDARequirement:
+ arv:OutputCollectionProperties:
+ outputProperties:
+ property1: value1
+ property2: $(inputs.value2)
+
+ cwltool:CUDARequirement:
cudaVersionMin: "11.0"
- cudaComputeCapabilityMin: "9.0"
- deviceCountMin: 1
- deviceCountMax: 1
+ cudaComputeCapability: "9.0"
+ cudaDeviceCountMin: 1
+ cudaDeviceCountMax: 1
+
+ arv:UsePreemptible:
+ usePreemptible: true
+
+ arv:OutOfMemoryRetry:
+ memoryRetryMultipler: 2
+ memoryErrorRegex: "custom memory error"
{% endcodeblock %}
h2(#RunInSingleContainer). arv:RunInSingleContainer
table(table table-bordered table-condensed).
|_. Field |_. Type |_. Description |
-|processProperties|key-value map, or list of objects with the fields {propertyName, propertyValue}|The properties that will be set on the container request. May include expressions that reference `$(inputs)` of the current workflow or tool.|
+|processProperties|key-value map, or list of objects with the fields {propertyName, propertyValue}|The properties that will be set on the container request. May include expressions that reference @$(inputs)@ of the current workflow or tool.|
+
+h2(#OutputCollectionProperties). arv:OutputCollectionProperties
+
+Specify custom "properties":{{site.baseurl}}/api/methods.html#subpropertyfilters that will be set on the output collection of the workflow step.
+
+table(table table-bordered table-condensed).
+|_. Field |_. Type |_. Description |
+|outputProperties|key-value map, or list of objects with the fields {propertyName, propertyValue}|The properties that will be set on the output collection. May include expressions that reference @$(inputs)@ of the current workflow or tool.|
-h2(#CUDARequirement). arv:CUDARequirement
+h2(#CUDARequirement). 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).
table(table table-bordered table-condensed).
|_. Field |_. Type |_. Description |
|cudaVersionMin|string|Required. The CUDA SDK version corresponding to the minimum driver version supported by the container (generally, the SDK version 'X.Y' the application was compiled against).|
-|cudaComputeCapabilityMin|string|Required. The minimum CUDA hardware capability (in 'X.Y' format) required by the application's PTX or C++ GPU code (will be JIT compiled for the available hardware).|
-|deviceCountMin|integer|Minimum number of GPU devices to allocate on a single node. Required.|
-|deviceCountMax|integer|Maximum number of GPU devices to allocate on a single node. Optional. If not specified, same as @minDeviceCount@.|
+|cudaComputeCapability|string|Required. The minimum CUDA hardware capability (in 'X.Y' format) required by the application's PTX or C++ GPU code (will be JIT compiled for the available hardware).|
+|cudaDeviceCountMin|integer|Minimum number of GPU devices to allocate on a single node. Required.|
+|cudaDeviceCountMax|integer|Maximum number of GPU devices to allocate on a single node. Optional. If not specified, same as @cudaDeviceCountMin@.|
+
+h2(#UsePreemptible). 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.
+
+table(table table-bordered table-condensed).
+|_. Field |_. Type |_. Description |
+|usePreemptible|boolean|Required, true to opt-in to using preemptible instances, false to opt-out.|
+
+
+h2(#OutOfMemoryRetry). 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 @memoryRetryMultipler@. 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.
+
+table(table table-bordered table-condensed).
+|_. Field |_. Type |_. Description |
+|memoryRetryMultipler|float|Required, the retry will multiply the base memory request by this factor to get the retry memory request.|
+|memoryErrorRegex|string|Optional, a custom regex that, if found in the stdout, stderr or crunch-run logging of a program, will trigger a retry with greater RAM. If not provided, the default pattern matches "out of memory" (with or without spaces), "memory error" (with or without spaces), "bad_alloc" and "container using over 90% of memory".|
h2. arv:dockerCollectionPDH
projects / arvados.git / blobdiff