Making drm_gpuvm work across gpu devices

Sat Jan 27 02:21:59 UTC 2024

Regarding the idea of expanding userptr to support migration, we explored this idea long time ago. It provides similar functions of the system allocator but its interface is not as convenient as system allocator. Besides the shared virtual address space, another benefit of a system allocator is, you can offload cpu program to gpu easier, you don’t need to call driver specific API (such as register_userptr and vm_bind in this case) for memory allocation.

We also scoped the implementation. It turned out to be big, and not as beautiful as hmm. Why we gave up this approach.

From: Christian König <christian.koenig at amd.com>
Sent: Friday, January 26, 2024 7:52 AM
To: Thomas Hellström <thomas.hellstrom at linux.intel.com>; Daniel Vetter <daniel at ffwll.ch>
Cc: Brost, Matthew <matthew.brost at intel.com>; Felix Kuehling <felix.kuehling at amd.com>; Welty, Brian <brian.welty at intel.com>; Ghimiray, Himal Prasad <himal.prasad.ghimiray at intel.com>; Zeng, Oak <oak.zeng at intel.com>; Gupta, saurabhg <saurabhg.gupta at intel.com>; Danilo Krummrich <dakr at redhat.com>; dri-devel at lists.freedesktop.org; Bommu, Krishnaiah <krishnaiah.bommu at intel.com>; Dave Airlie <airlied at redhat.com>; Vishwanathapura, Niranjana <niranjana.vishwanathapura at intel.com>; intel-xe at lists.freedesktop.org
Subject: Re: Making drm_gpuvm work across gpu devices

Am 26.01.24 um 09:21 schrieb Thomas Hellström:

Hi, all

On Thu, 2024-01-25 at 19:32 +0100, Daniel Vetter wrote:

On Wed, Jan 24, 2024 at 09:33:12AM +0100, Christian König wrote:

Am 23.01.24 um 20:37 schrieb Zeng, Oak:

[SNIP]

Yes most API are per device based.

One exception I know is actually the kfd SVM API. If you look at

the svm_ioctl function, it is per-process based. Each kfd_process

represent a process across N gpu devices.

Yeah and that was a big mistake in my opinion. We should really not

do that

ever again.

Need to say, kfd SVM represent a shared virtual address space

across CPU and all GPU devices on the system. This is by the

definition of SVM (shared virtual memory). This is very different

from our legacy gpu *device* driver which works for only one

device (i.e., if you want one device to access another device's

memory, you will have to use dma-buf export/import etc).

Exactly that thinking is what we have currently found as blocker

for a

virtualization projects. Having SVM as device independent feature

which

somehow ties to the process address space turned out to be an

extremely bad

idea.

The background is that this only works for some use cases but not

all of

them.

What's working much better is to just have a mirror functionality

which says

that a range A..B of the process address space is mapped into a

range C..D

of the GPU address space.

Those ranges can then be used to implement the SVM feature required

for

higher level APIs and not something you need at the UAPI or even

inside the

low level kernel memory management.

When you talk about migrating memory to a device you also do this

on a per

device basis and *not* tied to the process address space. If you

then get

crappy performance because userspace gave contradicting information

where to

migrate memory then that's a bug in userspace and not something the

kernel

should try to prevent somehow.

[SNIP]

I think if you start using the same drm_gpuvm for multiple

devices you

will sooner or later start to run into the same mess we have

seen with

KFD, where we moved more and more functionality from the KFD to

the DRM

render node because we found that a lot of the stuff simply

doesn't work

correctly with a single object to maintain the state.

As I understand it, KFD is designed to work across devices. A

single pseudo /dev/kfd device represent all hardware gpu devices.

That is why during kfd open, many pdd (process device data) is

created, each for one hardware device for this process.

Yes, I'm perfectly aware of that. And I can only repeat myself that

I see

this design as a rather extreme failure. And I think it's one of

the reasons

why NVidia is so dominant with Cuda.

This whole approach KFD takes was designed with the idea of

extending the

CPU process into the GPUs, but this idea only works for a few use

cases and

is not something we should apply to drivers in general.

A very good example are virtualization use cases where you end up

with CPU

address != GPU address because the VAs are actually coming from the

guest VM

and not the host process.

SVM is a high level concept of OpenCL, Cuda, ROCm etc.. This should

not have

any influence on the design of the kernel UAPI.

If you want to do something similar as KFD for Xe I think you need

to get

explicit permission to do this from Dave and Daniel and maybe even

Linus.

I think the one and only one exception where an SVM uapi like in kfd

makes

sense, is if the _hardware_ itself, not the software stack defined

semantics that you've happened to build on top of that hw, enforces a

1:1

mapping with the cpu process address space.

Which means your hardware is using PASID, IOMMU based translation,

PCI-ATS

(address translation services) or whatever your hw calls it and has

_no_

device-side pagetables on top. Which from what I've seen all devices

with

device-memory have, simply because they need some place to store

whether

that memory is currently in device memory or should be translated

using

PASID. Currently there's no gpu that works with PASID only, but there

are

some on-cpu-die accelerator things that do work like that.

Maybe in the future there will be some accelerators that are fully

cpu

cache coherent (including atomics) with something like CXL, and the

on-device memory is managed as normal system memory with struct page

as

ZONE_DEVICE and accelerator va -> physical address translation is

only

done with PASID ... but for now I haven't seen that, definitely not

in

upstream drivers.

And the moment you have some per-device pagetables or per-device

memory

management of some sort (like using gpuva mgr) then I'm 100% agreeing

with

Christian that the kfd SVM model is too strict and not a great idea.

Cheers, Sima

I'm trying to digest all the comments here, The end goal is to be able

to support something similar to this here:

https://developer.nvidia.com/blog/simplifying-gpu-application-development-with-heterogeneous-memory-management/

Christian, If I understand you correctly, you're strongly suggesting

not to try to manage a common virtual address space across different

devices in the kernel, but merely providing building blocks to do so,

like for example a generalized userptr with migration support using

HMM; That way each "mirror" of the CPU mm would be per device and

inserted into the gpu_vm just like any other gpu_vma, and user-space

would dictate the A..B -> C..D mapping by choosing the GPU_VA for the

vma.

Exactly that, yes.

Sima, it sounds like you're suggesting to shy away from hmm and not

even attempt to support this except if it can be done using IOMMU sva

on selected hardware?

I think that comment goes more into the direction of: If you have ATS/ATC/PRI capable hardware which exposes the functionality to make memory reads and writes directly into the address space of the CPU then yes an SVM only interface is ok because the hardware can't do anything else. But as long as you have something like GPUVM then please don't restrict yourself.

Which I totally agree on as well. The ATS/ATC/PRI combination doesn't allow using separate page tables device and CPU and so also not separate VAs.

This was one of the reasons why we stopped using this approach for AMD GPUs.

Regards,
Christian.

Could you clarify a bit?

Thanks,

Thomas

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