[PATCH] hmm: heterogeneous memory management documentation

[JÃrÃme Glisse]

This add documentation for HMM (Heterogeneous Memory Management). It
presents the motivation behind it, the features necessary for it to
be usefull and and gives an overview of how this is implemented.

Signed-off-by: Jéme Glisse <jglisse@xxxxxxxxxx>
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 Documentation/hmm.txt | 125 ++++++++++++++++++++++++++++++++++++++++++++++++++
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+Heterogeneous Memory Management (HMM)
+
+Transparently allow any component of a program to use any memory region of said
+program with a device without using device specific memory allocator. This is
+becoming a requirement to simplify the use of advance heterogeneous computing
+where GPU, DSP or FPGA are use to perform various computations.
+
+This document is divided as follow, in the first section i expose the problems
+related to the use of a device specific allocator. The second section i expose
+the hardware limitations that are inherent to many platforms. The third section
+gives an overview of HMM designs.
+
+
+-------------------------------------------------------------------------------
+
+1) Problems of using device specific memory allocator:
+
+Device with large amount of on board memory (several giga bytes) like GPU have
+historicaly manage their memory through dedicated driver specific API. This
+creates a disconnect between memory allocated and managed by device driver and
+regular application memory (private anonynous, share memory or regular file
+back memory). From here on i will refer to this aspect as split address space.
+I use share address space to refer to the opposite situation ie one in which
+any memory region can be use by device transparently.
+
+Split address space because device can only access memory allocated through the
+device specific API. This imply that all memory object in a program are not
+equal from device point of view which complicate large program that rely on a
+wide set of libraries.
+
+Concretly this means that code that wants to leverage device like GPU need to
+copy object between genericly allocated memory (malloc, mmap private/share/)
+and memory allocated through the device driver API (this still end up with an
+mmap but of the device file).
+
+For flat dataset (array, grid, image, ...) this isn't too hard to achieve but
+complex data-set (list, tree, ...) are hard to get right. Duplicating a complex
+data-set need to re-map all the pointer relations between each of its elements.
+This is error prone and program gets harder to debug because of the duplicate
+data-set.
+
+Split address space also means that library can not transparently use data they
+are getting from core program or other library and thus each library might have
+to duplicate its input data-set using specific memory allocator. Large project
+suffer from this and waste resources because of the various memory copy.
+
+Duplicating each library API to accept as input or output memory allocted by
+each device specific allocator is not a viable option. It would lead to a
+combinatorial explosions in the library entry points.
+
+Finaly with the advance of high level langage constructs (in C++ but in other
+langage too) it is now possible for compiler to leverage GPU or other devices
+without even the programmer knowledge. Some of compiler identified patterns are
+only do-able with a share address. It is as well more reasonable to use a share
+address space for all the other patterns.
+
+
+-------------------------------------------------------------------------------
+
+2) System bus, device memory characteristics
+
+System bus cripple share address due to few limitations. Most system bus only
+allow basic memory access from device to main memory, even cache coherency is
+often optional. Access to device memory from CPU is even more limited, most
+often than not it is not cache coherent.
+
+If we only consider the PCIE bus than device can access main memory (often
+through an IOMMU) and be cache coherent with the CPUs. However it only allows
+a limited set of atomic operation from device on main memory. This is worse
+in the other direction the CPUs can only access a limited range of the device
+memory and can not perform atomic operations on it. Thus device memory can not
+be consider like regular memory from kernel point of view.
+
+Another crippling factor is the limited bandwidth (~32GBytes/s with PCIE 4.0
+and 16 lanes). This is 33 times less that fastest GPU memory (1 TBytes/s).
+The final limitation is latency, access to main memory from the device has an
+order of magnitude higher latency than when the device access its own memory.
+
+Some platform are developing new system bus or additions/modifications to PCIE
+to address some of those limitations (OpenCAPI, CCIX). They mainly allow two
+way cache coherency between CPU and device and allow all atomic operations the
+architecture supports. Saddly not all platform are following this trends and
+some major architecture are left without hardware solutions to those problems.
+
+So for share address space to make sense not only we must allow device to
+access any memory memory but we must also permit any memory to be migrated to
+device memory while device is using it (blocking CPU access while it happens).
+
+
+-------------------------------------------------------------------------------
+
+3) Share address space and migration
+
+HMM intends to provide two main features. First one is to share the address
+space by duplication the CPU page table into the device page table so same
+address point to same memory and this for any valid main memory address in
+the process address space.
+
+To achieve this, HMM offer a set of helpers to populate the device page table
+while keeping track of CPU page table updates. Device page table updates are
+not as easy as CPU page table updates. To update the device page table you must
+allow a buffer (or use a pool of pre-allocated buffer) and write GPU specifics
+commands in it to perform the update (unmap, cache invalidations and flush,
+...). This can not be done through common code for all device. Hence why HMM
+provides helpers to factor out everything that can be while leaving the gory
+details to the device driver.
+
+The second mechanism HMM provide is a new kind of ZONE_DEVICE memory that does
+allow to allocate a struct page for each page of the device memory. Those page
+are special because the CPU can not map them. They however allow to migrate
+main memory to device memory using exhisting migration mechanism and everything
+looks like if page was swap out to disk from CPU point of view. Using a struct
+page gives the easiest and cleanest integration with existing mm mechanisms.
+Again here HMM only provide helpers, first to hotplug new ZONE_DEVICE memory
+for the device memory and second to perform migration. Policy decision of what
+and when to migrate things is left to the device driver.
+
+Note that any CPU acess to a device page trigger a page fault which initiate a
+migration back to system memory so that CPU can access it.
+
+
+With this two features, HMM not only allow a device to mirror a process address
+space and keeps both CPU and device page table synchronize, but also allow to
+leverage device memory by migrating part of data-set that is actively use by a
+device.
-- 
2.4.11


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