GPU device resource reservations with cgroups?
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- Subject: GPU device resource reservations with cgroups?
- From: Jeffrey Hugo <quic_jhugo@xxxxxxxxxxx>
- Date: Tue, 16 Aug 2022 14:39:52 -0600
- Cc: "linux-kernel@xxxxxxxxxxxxxxx" <linux-kernel@xxxxxxxxxxxxxxx>, dri-devel@xxxxxxxxxxxxxxxxxxxxx, quic_ajitpals@xxxxxxxxxxx, quic_pkanojiy@xxxxxxxxxxx, Carl Vanderlip <quic_carlv@xxxxxxxxxxx>, tjmercier@xxxxxxxxxx
- User-agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:91.0) Gecko/20100101 Thunderbird/91.6.0
Hello cgroup experts,
I have a GPU device [1] that supports organizing its resources for the
purposes of supporting containers. I am attempting to determine how to
represent this in the upstream kernel, and I wonder if it fits in cgroups.
The device itself has a number of resource types – compute cores,
memory, bus replicators, semaphores, and dma channels. Any particular
workload may consume some set of these resources. For example, a
workload may consume two compute cores, 1GB of memory, one dma channel,
but no semaphores and no bus replicators.
By default all of the resources are in a global pool. This global pool
is managed by the device firmware. Linux makes a request to the
firmware to load a workload. The firmware reads the resource
requirements from the workload itself, and then checks the global pool.
If the global pool contains sufficient resources to satisfy the needs of
the workload, the firmware assigns the required resources from the
global pool to the workload. If there are insufficient resources, the
workload request from Linux is rejected.
Some users may want to share the device between multiple containers, but
provide device level isolation between those containers. For example, a
user may have 4 workloads to run, one per container, and each workload
takes 1/4th of the set of compute cores. The user would like to reserve
sets of compute cores for each container so that container X always has
the expected set of resources available, and if container Y
malfunctions, it cannot “steal” resources from container X.
To support this, the firmware supports a concept of partitioning. A
partition is a pool of resources which are removed from the global pool,
and pre-assigned to the partition’s pool. A workload can then be run
from within a partition, and it consumes resources from that partition’s
pool instead of from the global pool. The firmware manages creating
partitions and assigning resources to them.
Partitions do not nest.
In the above user example, the user can create 4 partitions, and divide
up the compute cores among them. Then the user can assign each
individual container their own individual partition. Each container
would be limited to the resources within it’s assigned partition, but
also that container would have exclusive access to those resources.
This essentially provides isolation, and some Quality of Service (QoS).
How this is currently implemented (in downstream), is perhaps not ideal.
A privileged daemon process reads a configuration file which defines
the number of partitions, and the set of resources assigned to each.
That daemon makes requests to the firmware to create the partitions, and
gets a unique ID for each. Then the daemon makes a request to the
driver to create a “shadow device”, which is a child dev node. The
driver verifies with the firmware that the partition ID is valid, and
then creates the dev node. Internally the driver associates this shadow
device with the partition ID so that each request to the firmware is
tagged with the partition ID by the driver. This tagging allows the
firmware to determine that a request is targeted for a specific
partition. Finally, the shadow device is passed into the container,
instead of the normal dev node. The userspace within the container
operates the shadow device normally.
One concern with the current implementation is that it is possible to
create a large number of partitions. Since each partition is
represented by a shadow device dev node, this can create a large number
of dev nodes and exhaust the minor number space.
I wonder if this functionality is better represented by a cgroup.
Instead of creating a dev node for the partition, we can just run the
container process within the cgroup. However it doesn’t look like
cgroups have a concept of resource reservation. It is just a limit. If
that impression is accurate, then I struggle to see how to provide the
desired isolation as some entity not under the cgroup could consume all
of the device resources, leaving the containers unable to perform their
tasks.
So, cgroup experts, does this sound like something that should be
represented by a cgroup, or is cgroup the wrong mechanism for this usecase?
[1] -
https://lore.kernel.org/all/1660588956-24027-1-git-send-email-quic_jhugo@xxxxxxxxxxx/
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