Reserving CPU and memory
Each Modal container has a default reservation of 0.125 CPU cores and 128 MiB of memory. Containers can exceed this minimum if the worker has available CPU or memory. You can also guarantee access to more resources by requesting a higher reservation.
CPU cores
If you have code that must run on a larger number of cores, you can
request that using the cpu
argument. This allows you to specify a
floating-point number of CPU cores:
import modal
app = modal.App()
@app.function(cpu=8.0)
def my_function():
# code here will have access to at least 8.0 cores
...
Memory
If you have code that needs more guaranteed memory, you can request it using the
memory
argument. This expects an integer number of megabytes:
import modal
app = modal.App()
@app.function(memory=32768)
def my_function():
# code here will have access to at least 32 GiB of RAM
...
How much can I request?
For both CPU and memory, a maximum is enforced at function creation time to
ensure your application can be scheduled for execution. Requests exceeding the
maximum will be rejected with an
InvalidError
.
As the platform grows, we plan to support larger CPU and memory reservations.
Billing
For CPU and memory, you’ll be charged based on whichever is higher: your reservation or actual usage.
Disk requests are billed by increasing the memory request at a 20:1 ratio. For example, requesting 500 GiB of disk will increase the memory request to 25 GiB, if it is not already set higher.
Resource limits
CPU limits
Modal containers have a default soft CPU limit that is set at 4 physical cores above the CPU request. Given that the default CPU request is 0.125 cores the default soft CPU limit is 4.125 cores. Above this limit the host will begin to throttle the CPU usage of the container.
You can alternatively set the CPU limit explicitly.
cpu_request = 1.0
cpu_limit = 4.0
@app.function(cpu=(cpu_request, cpu_limit))
def f():
...
Memory limits
Modal containers can have a hard memory limit which will ‘Out of Memory’ (OOM) kill containers which attempt to exceed the limit. This functionality is useful when a container has a serious memory leak. You can set the limit and have the container killed to avoid paying for the leaked GBs of memory.
mem_request = 1024
mem_limit = 2048
@app.function(
memory=(mem_request, mem_limit),
)
def f():
...
Specify this limit using the memory
parameter on Modal Functions.
Disk limits
Running Modal containers have access to many GBs of SSD disk, but the amount of writes is limited by:
- The size of the underlying worker’s SSD disk capacity
- A per-container disk quota that is set in the 100s of GBs.
Hitting either limit will cause the container’s disk writes to be rejected, which
typically manifests as an OSError
.
Increased disk sizes can be requested with the ephemeral_disk
parameter. The maximum
disk size is 3.0 TiB (3,145,728 MiB). Larger disks are intended to be used for dataset processing.