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bffc33ec53
Patch series "HMM (Heterogeneous Memory Management)", v25.
Heterogeneous Memory Management (HMM) (description and justification)
Today device driver expose dedicated memory allocation API through their
device file, often relying on a combination of IOCTL and mmap calls.
The device can only access and use memory allocated through this API.
This effectively split the program address space into object allocated
for the device and useable by the device and other regular memory
(malloc, mmap of a file, share memory, â) only accessible by
CPU (or in a very limited way by a device by pinning memory).
Allowing different isolated component of a program to use a device thus
require duplication of the input data structure using device memory
allocator. This is reasonable for simple data structure (array, grid,
image, â) but this get extremely complex with advance data
structure (list, tree, graph, â) that rely on a web of memory
pointers. This is becoming a serious limitation on the kind of work
load that can be offloaded to device like GPU.
New industry standard like C++, OpenCL or CUDA are pushing to remove
this barrier. This require a shared address space between GPU device
and CPU so that GPU can access any memory of a process (while still
obeying memory protection like read only). This kind of feature is also
appearing in various other operating systems.
HMM is a set of helpers to facilitate several aspects of address space
sharing and device memory management. Unlike existing sharing mechanism
that rely on pining pages use by a device, HMM relies on mmu_notifier to
propagate CPU page table update to device page table.
Duplicating CPU page table is only one aspect necessary for efficiently
using device like GPU. GPU local memory have bandwidth in the TeraBytes/
second range but they are connected to main memory through a system bus
like PCIE that is limited to 32GigaBytes/second (PCIE 4.0 16x). Thus it
is necessary to allow migration of process memory from main system memory
to device memory. Issue is that on platform that only have PCIE the
device memory is not accessible by the CPU with the same properties as
main memory (cache coherency, atomic operations, ...).
To allow migration from main memory to device memory HMM provides a set of
helper to hotplug device memory as a new type of ZONE_DEVICE memory which
is un-addressable by CPU but still has struct page representing it. This
allow most of the core kernel logic that deals with a process memory to
stay oblivious of the peculiarity of device memory.
When page backing an address of a process is migrated to device memory the
CPU page table entry is set to a new specific swap entry. CPU access to
such address triggers a migration back to system memory, just like if the
page was swap on disk. HMM also blocks any one from pinning a ZONE_DEVICE
page so that it can always be migrated back to system memory if CPU access
it. Conversely HMM does not migrate to device memory any page that is pin
in system memory.
To allow efficient migration between device memory and main memory a new
migrate_vma() helpers is added with this patchset. It allows to leverage
device DMA engine to perform the copy operation.
This feature will be use by upstream driver like nouveau mlx5 and probably
other in the future (amdgpu is next suspect in line). We are actively
working on nouveau and mlx5 support. To test this patchset we also worked
with NVidia close source driver team, they have more resources than us to
test this kind of infrastructure and also a bigger and better userspace
eco-system with various real industry workload they can be use to test and
profile HMM.
The expected workload is a program builds a data set on the CPU (from
disk, from network, from sensors, â). Program uses GPU API (OpenCL,
CUDA, ...) to give hint on memory placement for the input data and also
for the output buffer. Program call GPU API to schedule a GPU job, this
happens using device driver specific ioctl. All this is hidden from
programmer point of view in case of C++ compiler that transparently
offload some part of a program to GPU. Program can keep doing other stuff
on the CPU while the GPU is crunching numbers.
It is expected that CPU will not access the same data set as the GPU while
GPU is working on it, but this is not mandatory. In fact we expect some
small memory object to be actively access by both GPU and CPU concurrently
as synchronization channel and/or for monitoring purposes. Such object
will stay in system memory and should not be bottlenecked by system bus
bandwidth (rare write and read access from both CPU and GPU).
As we are relying on device driver API, HMM does not introduce any new
syscall nor does it modify any existing ones. It does not change any
POSIX semantics or behaviors. For instance the child after a fork of a
process that is using HMM will not be impacted in anyway, nor is there any
data hazard between child COW or parent COW of memory that was migrated to
device prior to fork.
HMM assume a numbers of hardware features. Device must allow device page
table to be updated at any time (ie device job must be preemptable).
Device page table must provides memory protection such as read only.
Device must track write access (dirty bit). Device must have a minimum
granularity that match PAGE_SIZE (ie 4k).
Reviewer (just hint):
Patch 1 HMM documentation
Patch 2 introduce core infrastructure and definition of HMM, pretty
small patch and easy to review
Patch 3 introduce the mirror functionality of HMM, it relies on
mmu_notifier and thus someone familiar with that part would be
in better position to review
Patch 4 is an helper to snapshot CPU page table while synchronizing with
concurrent page table update. Understanding mmu_notifier makes
review easier.
Patch 5 is mostly a wrapper around handle_mm_fault()
Patch 6 add new add_pages() helper to avoid modifying each arch memory
hot plug function
Patch 7 add a new memory type for ZONE_DEVICE and also add all the logic
in various core mm to support this new type. Dan Williams and
any core mm contributor are best people to review each half of
this patchset
Patch 8 special case HMM ZONE_DEVICE pages inside put_page() Kirill and
Dan Williams are best person to review this
Patch 9 allow to uncharge a page from memory group without using the lru
list field of struct page (best reviewer: Johannes Weiner or
Vladimir Davydov or Michal Hocko)
Patch 10 Add support to uncharge ZONE_DEVICE page from a memory cgroup (best
reviewer: Johannes Weiner or Vladimir Davydov or Michal Hocko)
Patch 11 add helper to hotplug un-addressable device memory as new type
of ZONE_DEVICE memory (new type introducted in patch 3 of this
serie). This is boiler plate code around memory hotplug and it
also pick a free range of physical address for the device memory.
Note that the physical address do not point to anything (at least
as far as the kernel knows).
Patch 12 introduce a new hmm_device class as an helper for device driver
that want to expose multiple device memory under a common fake
device driver. This is usefull for multi-gpu configuration.
Anyone familiar with device driver infrastructure can review
this. Boiler plate code really.
Patch 13 add a new migrate mode. Any one familiar with page migration is
welcome to review.
Patch 14 introduce a new migration helper (migrate_vma()) that allow to
migrate a range of virtual address of a process using device DMA
engine to perform the copy. It is not limited to do copy from and
to device but can also do copy between any kind of source and
destination memory. Again anyone familiar with migration code
should be able to verify the logic.
Patch 15 optimize the new migrate_vma() by unmapping pages while we are
collecting them. This can be review by any mm folks.
Patch 16 add unaddressable memory migration to helper introduced in patch
7, this can be review by anyone familiar with migration code
Patch 17 add a feature that allow device to allocate non-present page on
the GPU when migrating a range of address to device memory. This
is an helper for device driver to avoid having to first allocate
system memory before migration to device memory
Patch 18 add a new kind of ZONE_DEVICE memory for cache coherent device
memory (CDM)
Patch 19 add an helper to hotplug CDM memory
Previous patchset posting :
v1 http://lwn.net/Articles/597289/
v2 https://lkml.org/lkml/2014/6/12/559
v3 https://lkml.org/lkml/2014/6/13/633
v4 https://lkml.org/lkml/2014/8/29/423
v5 https://lkml.org/lkml/2014/11/3/759
v6 http://lwn.net/Articles/619737/
v7 http://lwn.net/Articles/627316/
v8 https://lwn.net/Articles/645515/
v9 https://lwn.net/Articles/651553/
v10 https://lwn.net/Articles/654430/
v11 http://www.gossamer-threads.com/lists/linux/kernel/2286424
v12 http://www.kernelhub.org/?msg=972982&p=2
v13 https://lwn.net/Articles/706856/
v14 https://lkml.org/lkml/2016/12/8/344
v15 http://www.mail-archive.com/linux-kernel@xxxxxxxxxxxxxxx/msg1304107.html
v16 http://www.spinics.net/lists/linux-mm/msg119814.html
v17 https://lkml.org/lkml/2017/1/27/847
v18 https://lkml.org/lkml/2017/3/16/596
v19 https://lkml.org/lkml/2017/4/5/831
v20 https://lwn.net/Articles/720715/
v21 https://lkml.org/lkml/2017/4/24/747
v22 http://lkml.iu.edu/hypermail/linux/kernel/1705.2/05176.html
v23 https://www.mail-archive.com/linux-kernel@vger.kernel.org/msg1404788.html
v24 https://lwn.net/Articles/726691/
This patch (of 19):
This adds documentation for HMM (Heterogeneous Memory Management). It
presents the motivation behind it, the features necessary for it to be
useful and and gives an overview of how this is implemented.
Link: http://lkml.kernel.org/r/20170817000548.32038-2-jglisse@redhat.com
Signed-off-by: Jérôme Glisse <jglisse@redhat.com>
Cc: John Hubbard <jhubbard@nvidia.com>
Cc: Dan Williams <dan.j.williams@intel.com>
Cc: David Nellans <dnellans@nvidia.com>
Cc: Balbir Singh <bsingharora@gmail.com>
Cc: Aneesh Kumar <aneesh.kumar@linux.vnet.ibm.com>
Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org>
Cc: Evgeny Baskakov <ebaskakov@nvidia.com>
Cc: Johannes Weiner <hannes@cmpxchg.org>
Cc: Kirill A. Shutemov <kirill.shutemov@linux.intel.com>
Cc: Mark Hairgrove <mhairgrove@nvidia.com>
Cc: Michal Hocko <mhocko@kernel.org>
Cc: Paul E. McKenney <paulmck@linux.vnet.ibm.com>
Cc: Ross Zwisler <ross.zwisler@linux.intel.com>
Cc: Sherry Cheung <SCheung@nvidia.com>
Cc: Subhash Gutti <sgutti@nvidia.com>
Cc: Vladimir Davydov <vdavydov.dev@gmail.com>
Cc: Bob Liu <liubo95@huawei.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
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