Re: [HMM 00/16] HMM (Heterogeneous Memory Management) v18

[Jerome Glisse <jglisse@redhat.com>]

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On Thu, Mar 16, 2017 at 01:43:21PM -0700, Andrew Morton wrote:
> On Thu, 16 Mar 2017 12:05:19 -0400 J__r__me Glisse <jglisse@redhat.com> wrote:
> 
> > Cliff note:
> 
> "Cliff's notes" isn't appropriate for a large feature such as this. 
> Where's the long-form description?  One which permits readers to fully
> understand the requirements, design, alternative designs, the
> implementation, the interface(s), etc?
> 
> Have you ever spoken about HMM at a conference?  If so, the supporting
> presentation documents might help here.  That's the level of detail
> which should be presented here.

Longer description of patchset rational, motivation and design choices
were given in the first few posting of the patchset to which i included
a link in my cover letter. Also given that i presented that for last 3
or 4 years to mm summit and kernel summit i thought that by now peoples
were familiar about the topic and wanted to spare them the long version.
My bad.

I attach a patch that is a first stab at a Documentation/hmm.txt that
explain the motivation and rational behind HMM. I can probably add a
section about how to use HMM from device driver point of view.


> > HMM offers 2 things (each standing on its own). First
> > it allows to use device memory transparently inside any process
> > without any modifications to process program code.
> 
> Well.  What is "device memory"?  That's very vague.  What are the
> characteristics of this memory?  Why is it a requirement that
> userspace code be unaltered?  What are the security implications - does
> the process need particular permissions to access this memory?  What is
> the proposed interface to set up this access?

Thing like GPU memory, think 16GBytes, 32GBytes with 1TeraBytes/s of
bandwidth so something that is just completely in a different category
than DDR3/DDR4 or PCIE bandwidth.

To allow GPU/FPGA/... to be transparently use by program we need to
avoid any requirement to modify any code. Advance in high level langage
construct (in C++ but others too) gives opportunities to compiler to
leverage GPU transparently without programmer knowledge. But for this
to happen we need a share address space ie any pointer in program must
be accessible by the device and we must also be able to migrate memory
to device memory to benefit from the device memory bandwidth.

Moreover if you think about complex software that use a plethora of
various library, you want to allow some of the library to leverage GPU
or DSP transparently without forcing the library to copy/duplicate its
input data which can be highly complex if you think of tree, list, ...
Making all this transparent from program/library point of view ease
the development of thoses. Quite frankly without that it is border line
impossible to efficiently use GPU or other device in many cases.

The device memory is treated like regular memory from kernel point of
view (except that CPU can not access it) but everything else about page
holds (read, write, execution protections ...). So there is no security
implications. Device under consideration have page table and works like
CPU from process isolation point of view (modulo hardware bug but CPU
or main memory have those same issues).


There is no propose interface here, nor i see a need for one. When the
device starts accessing a range of the process address space the device
driver can decide to migrate that range to device memory in order to
speed computations. Only the device driver has enough informations on
wether or not this is a good idea and this changes continously during
run time (depends on what other process are doing ...).

So for now like it was discuss in some CDM threads and in some previous
HMM threads i believe it is better to let the device driver decide and
keep HMM out of any policy choices. Latter down the road once we get more
devices and more real world usage we can try to figure out if there is
a good way to expose a generic memory placement hint to userspace to
allow program to improve performances by helping device driver to make
better decissions.

 
> > Second it allows to mirror process address space on a device.
> 
> Why?  Why is this a requirement, how will it be used, what are the
> use cases, etc?

>From above, the requirement is that any address the CPU can access could
also be access by the device with the same restriction (like read/write
protection). This greatly simplify use of such device, either transparently
by the compiler without programmer knowledge or through some library again
without main program developer knowledge. The whole point is to make it
easier to use thing like GPU without having to ask developer to use
special memory allocator and to duplicate their dataset.


> 
> I spent a bit of time trying to locate a decent writeup of this feature
> but wasn't able to locate one.  I'm not seeing a Documentation/ update
> in this patchset.  Perhaps if you were to sit down and write a detailed
> Documentation/vm/hmm.txt then that would be a good starting point.

Attach is hmm.txt like i said i thought that all the previous at length
description that i have given in the numerous posting of the patchset
were enough and that i only needed to refresh peoples memory.

> 
> This stuff is important - it's not really feasible to perform a decent
> review of this proposal unless the reviewer has access to this
> high-level conceptual stuff.

Does the above and the attach documentation answer your questions ? Is
there thing i should describe more thouroughly or aspect you feel are
missing ?

Cheers,
Jérôme

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>From 4a2cb2211af22b6b149ba9afebc27f8d5763bac2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?J=C3=A9r=C3=B4me=20Glisse?= <jglisse@redhat.com>
Date: Thu, 16 Mar 2017 20:27:43 -0400
Subject: [PATCH] hmm: heterogeneous memory management documentation
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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: Jérôme Glisse <jglisse@redhat.com>
---
 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.
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