Runtime attributes can be configured within a WDL's task block, but if no value is specified for any one of the customizable attributes your task will run with the default runtime attribute value. The chart below shows the defaults for each runtime attribute, and how to customize to a value of your choosing.
For more information on runtime attributes, please see Cromwell's Runtime Attribute Descriptions documentation.
Terra supports the following CPU platforms:
- Intel Cascade Lake (n2)
- Intel Skylake (n1)
- Intel Broadwell (n1)
- Intel Haswell (n1)
- Intel Ivy Bridge (n1)
- Intel Sandy Bridge (n1)
- AMD Rome (n2d)
Terra will request a custom Google VM based on your specification. Please see the notes for CPU and memory to learn how Google interprets your resource request. See Google's documentation for more information about their machine families and rules for custom machines.
|
Runtime attribute |
Default | How to customize |
| Region of Workflow VM | us-central1 |
runtime { To learn more about available regions, click here |
| Zone of Workflow VM | us-central1-b |
runtime { To learn more about available zones, click here |
| CPU | 1 |
runtime { For more details on CPU quotas, see this article n1 machines can have 1-6.5 GB of memory per CPU. n2 and n2d machines can have 0.5-8 GB of memory per CPU. |
| cpuPlatform | Whichever variety of CPU Platform n1 machine Google has available at time of request |
runtime { |
| memory | 2G |
runtime {
Google Cloud interprets this as the minimum amount of memory to use. If you request more CPUs than makes sense for your memory request, Google will automatically bump up to the appropriate amount of memory. Example: You cannot request 8 CPUs and 1 GB memory, since each CPU needs between 1-6.5 GB of memory. |
| disks | 10GB SSD |
runtime { |
| bootDiskSizeGb | 10GB |
runtime { |
| maxRetries | 0 | runtime { maxRetries: 3 } |
| preemptible | 0 |
runtime { For more details on saving costs with preemptible VMs, see this article |
| GPUs | not used |
runtime { For more details on using GPUs, see this article |