3 =====================================
4 Heterogeneous Memory Management (HMM)
5 =====================================
7 Provide infrastructure and helpers to integrate non-conventional memory (device
8 memory like GPU on board memory) into regular kernel path, with the cornerstone
9 of this being specialized struct page for such memory (see sections 5 to 7 of
12 HMM also provides optional helpers for SVM (Share Virtual Memory), i.e.,
13 allowing a device to transparently access program addresses coherently with
14 the CPU meaning that any valid pointer on the CPU is also a valid pointer
15 for the device. This is becoming mandatory to simplify the use of advanced
16 heterogeneous computing where GPU, DSP, or FPGA are used to perform various
17 computations on behalf of a process.
19 This document is divided as follows: in the first section I expose the problems
20 related to using device specific memory allocators. In the second section, I
21 expose the hardware limitations that are inherent to many platforms. The third
22 section gives an overview of the HMM design. The fourth section explains how
23 CPU page-table mirroring works and the purpose of HMM in this context. The
24 fifth section deals with how device memory is represented inside the kernel.
25 Finally, the last section presents a new migration helper that allows
26 leveraging the device DMA engine.
30 Problems of using a device specific memory allocator
31 ====================================================
33 Devices with a large amount of on board memory (several gigabytes) like GPUs
34 have historically managed their memory through dedicated driver specific APIs.
35 This creates a disconnect between memory allocated and managed by a device
36 driver and regular application memory (private anonymous, shared memory, or
37 regular file backed memory). From here on I will refer to this aspect as split
38 address space. I use shared address space to refer to the opposite situation:
39 i.e., one in which any application memory region can be used by a device
42 Split address space happens because devices can only access memory allocated
43 through a device specific API. This implies that all memory objects in a program
44 are not equal from the device point of view which complicates large programs
45 that rely on a wide set of libraries.
47 Concretely, this means that code that wants to leverage devices like GPUs needs
48 to copy objects between generically allocated memory (malloc, mmap private, mmap
49 share) and memory allocated through the device driver API (this still ends up
50 with an mmap but of the device file).
52 For flat data sets (array, grid, image, ...) this isn't too hard to achieve but
53 for complex data sets (list, tree, ...) it's hard to get right. Duplicating a
54 complex data set needs to re-map all the pointer relations between each of its
55 elements. This is error prone and programs get harder to debug because of the
56 duplicate data set and addresses.
58 Split address space also means that libraries cannot transparently use data
59 they are getting from the core program or another library and thus each library
60 might have to duplicate its input data set using the device specific memory
61 allocator. Large projects suffer from this and waste resources because of the
62 various memory copies.
64 Duplicating each library API to accept as input or output memory allocated by
65 each device specific allocator is not a viable option. It would lead to a
66 combinatorial explosion in the library entry points.
68 Finally, with the advance of high level language constructs (in C++ but in
69 other languages too) it is now possible for the compiler to leverage GPUs and
70 other devices without programmer knowledge. Some compiler identified patterns
71 are only do-able with a shared address space. It is also more reasonable to use
72 a shared address space for all other patterns.
75 I/O bus, device memory characteristics
76 ======================================
78 I/O buses cripple shared address spaces due to a few limitations. Most I/O
79 buses only allow basic memory access from device to main memory; even cache
80 coherency is often optional. Access to device memory from a CPU is even more
81 limited. More often than not, it is not cache coherent.
83 If we only consider the PCIE bus, then a device can access main memory (often
84 through an IOMMU) and be cache coherent with the CPUs. However, it only allows
85 a limited set of atomic operations from the device on main memory. This is worse
86 in the other direction: the CPU can only access a limited range of the device
87 memory and cannot perform atomic operations on it. Thus device memory cannot
88 be considered the same as regular memory from the kernel point of view.
90 Another crippling factor is the limited bandwidth (~32GBytes/s with PCIE 4.0
91 and 16 lanes). This is 33 times less than the fastest GPU memory (1 TBytes/s).
92 The final limitation is latency. Access to main memory from the device has an
93 order of magnitude higher latency than when the device accesses its own memory.
95 Some platforms are developing new I/O buses or additions/modifications to PCIE
96 to address some of these limitations (OpenCAPI, CCIX). They mainly allow
97 two-way cache coherency between CPU and device and allow all atomic operations the
98 architecture supports. Sadly, not all platforms are following this trend and
99 some major architectures are left without hardware solutions to these problems.
101 So for shared address space to make sense, not only must we allow devices to
102 access any memory but we must also permit any memory to be migrated to device
103 memory while the device is using it (blocking CPU access while it happens).
106 Shared address space and migration
107 ==================================
109 HMM intends to provide two main features. The first one is to share the address
110 space by duplicating the CPU page table in the device page table so the same
111 address points to the same physical memory for any valid main memory address in
112 the process address space.
114 To achieve this, HMM offers a set of helpers to populate the device page table
115 while keeping track of CPU page table updates. Device page table updates are
116 not as easy as CPU page table updates. To update the device page table, you must
117 allocate a buffer (or use a pool of pre-allocated buffers) and write GPU
118 specific commands in it to perform the update (unmap, cache invalidations, and
119 flush, ...). This cannot be done through common code for all devices. Hence
120 why HMM provides helpers to factor out everything that can be while leaving the
121 hardware specific details to the device driver.
123 The second mechanism HMM provides is a new kind of ZONE_DEVICE memory that
124 allows allocating a struct page for each page of device memory. Those pages
125 are special because the CPU cannot map them. However, they allow migrating
126 main memory to device memory using existing migration mechanisms and everything
127 looks like a page that is swapped out to disk from the CPU point of view. Using a
128 struct page gives the easiest and cleanest integration with existing mm
129 mechanisms. Here again, HMM only provides helpers, first to hotplug new ZONE_DEVICE
130 memory for the device memory and second to perform migration. Policy decisions
131 of what and when to migrate is left to the device driver.
133 Note that any CPU access to a device page triggers a page fault and a migration
134 back to main memory. For example, when a page backing a given CPU address A is
135 migrated from a main memory page to a device page, then any CPU access to
136 address A triggers a page fault and initiates a migration back to main memory.
138 With these two features, HMM not only allows a device to mirror process address
139 space and keeps both CPU and device page tables synchronized, but also
140 leverages device memory by migrating the part of the data set that is actively being
144 Address space mirroring implementation and API
145 ==============================================
147 Address space mirroring's main objective is to allow duplication of a range of
148 CPU page table into a device page table; HMM helps keep both synchronized. A
149 device driver that wants to mirror a process address space must start with the
150 registration of a mmu_interval_notifier::
152 int mmu_interval_notifier_insert(struct mmu_interval_notifier *interval_sub,
153 struct mm_struct *mm, unsigned long start,
154 unsigned long length,
155 const struct mmu_interval_notifier_ops *ops);
157 During the ops->invalidate() callback the device driver must perform the
158 update action to the range (mark range read only, or fully unmap, etc.). The
159 device must complete the update before the driver callback returns.
161 When the device driver wants to populate a range of virtual addresses, it can
164 long hmm_range_fault(struct hmm_range *range, unsigned int flags);
166 With the HMM_RANGE_SNAPSHOT flag, it will only fetch present CPU page table
167 entries and will not trigger a page fault on missing or non-present entries.
168 Without that flag, it does trigger a page fault on missing or read-only entries
169 if write access is requested (see below). Page faults use the generic mm page
170 fault code path just like a CPU page fault.
172 Both functions copy CPU page table entries into their pfns array argument. Each
173 entry in that array corresponds to an address in the virtual range. HMM
174 provides a set of flags to help the driver identify special CPU page table
177 Locking within the sync_cpu_device_pagetables() callback is the most important
178 aspect the driver must respect in order to keep things properly synchronized.
179 The usage pattern is::
181 int driver_populate_range(...)
183 struct hmm_range range;
186 range.notifier = &interval_sub;
192 range.pfn_shift = ...;
194 if (!mmget_not_zero(interval_sub->notifier.mm))
198 range.notifier_seq = mmu_interval_read_begin(&interval_sub);
199 down_read(&mm->mmap_sem);
200 ret = hmm_range_fault(&range, HMM_RANGE_SNAPSHOT);
202 up_read(&mm->mmap_sem);
207 up_read(&mm->mmap_sem);
209 take_lock(driver->update);
210 if (mmu_interval_read_retry(&ni, range.notifier_seq) {
211 release_lock(driver->update);
215 /* Use pfns array content to update device page table,
216 * under the update lock */
218 release_lock(driver->update);
222 The driver->update lock is the same lock that the driver takes inside its
223 invalidate() callback. That lock must be held before calling
224 mmu_interval_read_retry() to avoid any race with a concurrent CPU page table
227 Leverage default_flags and pfn_flags_mask
228 =========================================
230 The hmm_range struct has 2 fields, default_flags and pfn_flags_mask, that specify
231 fault or snapshot policy for the whole range instead of having to set them
232 for each entry in the pfns array.
234 For instance, if the device flags for range.flags are::
236 range.flags[HMM_PFN_VALID] = (1 << 63);
237 range.flags[HMM_PFN_WRITE] = (1 << 62);
239 and the device driver wants pages for a range with at least read permission,
242 range->default_flags = (1 << 63);
243 range->pfn_flags_mask = 0;
245 and calls hmm_range_fault() as described above. This will fill fault all pages
246 in the range with at least read permission.
248 Now let's say the driver wants to do the same except for one page in the range for
249 which it wants to have write permission. Now driver set::
251 range->default_flags = (1 << 63);
252 range->pfn_flags_mask = (1 << 62);
253 range->pfns[index_of_write] = (1 << 62);
255 With this, HMM will fault in all pages with at least read (i.e., valid) and for the
256 address == range->start + (index_of_write << PAGE_SHIFT) it will fault with
257 write permission i.e., if the CPU pte does not have write permission set then HMM
258 will call handle_mm_fault().
260 Note that HMM will populate the pfns array with write permission for any page
261 that is mapped with CPU write permission no matter what values are set
262 in default_flags or pfn_flags_mask.
265 Represent and manage device memory from core kernel point of view
266 =================================================================
268 Several different designs were tried to support device memory. The first one
269 used a device specific data structure to keep information about migrated memory
270 and HMM hooked itself in various places of mm code to handle any access to
271 addresses that were backed by device memory. It turns out that this ended up
272 replicating most of the fields of struct page and also needed many kernel code
273 paths to be updated to understand this new kind of memory.
275 Most kernel code paths never try to access the memory behind a page
276 but only care about struct page contents. Because of this, HMM switched to
277 directly using struct page for device memory which left most kernel code paths
278 unaware of the difference. We only need to make sure that no one ever tries to
279 map those pages from the CPU side.
281 Migration to and from device memory
282 ===================================
284 Because the CPU cannot access device memory, migration must use the device DMA
285 engine to perform copy from and to device memory. For this we need to use
286 migrate_vma_setup(), migrate_vma_pages(), and migrate_vma_finalize() helpers.
289 Memory cgroup (memcg) and rss accounting
290 ========================================
292 For now, device memory is accounted as any regular page in rss counters (either
293 anonymous if device page is used for anonymous, file if device page is used for
294 file backed page, or shmem if device page is used for shared memory). This is a
295 deliberate choice to keep existing applications, that might start using device
296 memory without knowing about it, running unimpacted.
298 A drawback is that the OOM killer might kill an application using a lot of
299 device memory and not a lot of regular system memory and thus not freeing much
300 system memory. We want to gather more real world experience on how applications
301 and system react under memory pressure in the presence of device memory before
302 deciding to account device memory differently.
305 Same decision was made for memory cgroup. Device memory pages are accounted
306 against same memory cgroup a regular page would be accounted to. This does
307 simplify migration to and from device memory. This also means that migration
308 back from device memory to regular memory cannot fail because it would
309 go above memory cgroup limit. We might revisit this choice latter on once we
310 get more experience in how device memory is used and its impact on memory
314 Note that device memory can never be pinned by a device driver nor through GUP
315 and thus such memory is always free upon process exit. Or when last reference
316 is dropped in case of shared memory or file backed memory.