mm: shuffle initial free memory to improve memory-side-cache utilization
Patch series "mm: Randomize free memory", v10.
This patch (of 3):
Randomization of the page allocator improves the average utilization of
a direct-mapped memory-side-cache. Memory side caching is a platform
capability that Linux has been previously exposed to in HPC
(high-performance computing) environments on specialty platforms. In
that instance it was a smaller pool of high-bandwidth-memory relative to
higher-capacity / lower-bandwidth DRAM. Now, this capability is going
to be found on general purpose server platforms where DRAM is a cache in
front of higher latency persistent memory [1].
Robert offered an explanation of the state of the art of Linux
interactions with memory-side-caches [2], and I copy it here:
It's been a problem in the HPC space:
http://www.nersc.gov/research-and-development/knl-cache-mode-performance-coe/
A kernel module called zonesort is available to try to help:
https://software.intel.com/en-us/articles/xeon-phi-software
and this abandoned patch series proposed that for the kernel:
https://lkml.kernel.org/r/20170823100205.17311-1-lukasz.daniluk@intel.com
Dan's patch series doesn't attempt to ensure buffers won't conflict, but
also reduces the chance that the buffers will. This will make performance
more consistent, albeit slower than "optimal" (which is near impossible
to attain in a general-purpose kernel). That's better than forcing
users to deploy remedies like:
"To eliminate this gradual degradation, we have added a Stream
measurement to the Node Health Check that follows each job;
nodes are rebooted whenever their measured memory bandwidth
falls below 300 GB/s."
A replacement for zonesort was merged upstream in commit cc9aec03e58f
("x86/numa_emulation: Introduce uniform split capability"). With this
numa_emulation capability, memory can be split into cache sized
("near-memory" sized) numa nodes. A bind operation to such a node, and
disabling workloads on other nodes, enables full cache performance.
However, once the workload exceeds the cache size then cache conflicts
are unavoidable. While HPC environments might be able to tolerate
time-scheduling of cache sized workloads, for general purpose server
platforms, the oversubscribed cache case will be the common case.
The worst case scenario is that a server system owner benchmarks a
workload at boot with an un-contended cache only to see that performance
degrade over time, even below the average cache performance due to
excessive conflicts. Randomization clips the peaks and fills in the
valleys of cache utilization to yield steady average performance.
Here are some performance impact details of the patches:
1/ An Intel internal synthetic memory bandwidth measurement tool, saw a
3X speedup in a contrived case that tries to force cache conflicts.
The contrived cased used the numa_emulation capability to force an
instance of the benchmark to be run in two of the near-memory sized
numa nodes. If both instances were placed on the same emulated they
would fit and cause zero conflicts. While on separate emulated nodes
without randomization they underutilized the cache and conflicted
unnecessarily due to the in-order allocation per node.
2/ A well known Java server application benchmark was run with a heap
size that exceeded cache size by 3X. The cache conflict rate was 8%
for the first run and degraded to 21% after page allocator aging. With
randomization enabled the rate levelled out at 11%.
3/ A MongoDB workload did not observe measurable difference in
cache-conflict rates, but the overall throughput dropped by 7% with
randomization in one case.
4/ Mel Gorman ran his suite of performance workloads with randomization
enabled on platforms without a memory-side-cache and saw a mix of some
improvements and some losses [3].
While there is potentially significant improvement for applications that
depend on low latency access across a wide working-set, the performance
may be negligible to negative for other workloads. For this reason the
shuffle capability defaults to off unless a direct-mapped
memory-side-cache is detected. Even then, the page_alloc.shuffle=0
parameter can be specified to disable the randomization on those systems.
Outside of memory-side-cache utilization concerns there is potentially
security benefit from randomization. Some data exfiltration and
return-oriented-programming attacks rely on the ability to infer the
location of sensitive data objects. The kernel page allocator, especially
early in system boot, has predictable first-in-first out behavior for
physical pages. Pages are freed in physical address order when first
onlined.
Quoting Kees:
"While we already have a base-address randomization
(CONFIG_RANDOMIZE_MEMORY), attacks against the same hardware and
memory layouts would certainly be using the predictability of
allocation ordering (i.e. for attacks where the base address isn't
important: only the relative positions between allocated memory).
This is common in lots of heap-style attacks. They try to gain
control over ordering by spraying allocations, etc.
I'd really like to see this because it gives us something similar
to CONFIG_SLAB_FREELIST_RANDOM but for the page allocator."
While SLAB_FREELIST_RANDOM reduces the predictability of some local slab
caches it leaves vast bulk of memory to be predictably in order allocated.
However, it should be noted, the concrete security benefits are hard to
quantify, and no known CVE is mitigated by this randomization.
Introduce shuffle_free_memory(), and its helper shuffle_zone(), to perform
a Fisher-Yates shuffle of the page allocator 'free_area' lists when they
are initially populated with free memory at boot and at hotplug time. Do
this based on either the presence of a page_alloc.shuffle=Y command line
parameter, or autodetection of a memory-side-cache (to be added in a
follow-on patch).
The shuffling is done in terms of CONFIG_SHUFFLE_PAGE_ORDER sized free
pages where the default CONFIG_SHUFFLE_PAGE_ORDER is MAX_ORDER-1 i.e. 10,
4MB this trades off randomization granularity for time spent shuffling.
MAX_ORDER-1 was chosen to be minimally invasive to the page allocator
while still showing memory-side cache behavior improvements, and the
expectation that the security implications of finer granularity
randomization is mitigated by CONFIG_SLAB_FREELIST_RANDOM. The
performance impact of the shuffling appears to be in the noise compared to
other memory initialization work.
This initial randomization can be undone over time so a follow-on patch is
introduced to inject entropy on page free decisions. It is reasonable to
ask if the page free entropy is sufficient, but it is not enough due to
the in-order initial freeing of pages. At the start of that process
putting page1 in front or behind page0 still keeps them close together,
page2 is still near page1 and has a high chance of being adjacent. As
more pages are added ordering diversity improves, but there is still high
page locality for the low address pages and this leads to no significant
impact to the cache conflict rate.
[1]: https://itpeernetwork.intel.com/intel-optane-dc-persistent-memory-operating-modes/
[2]: https://lkml.kernel.org/r/AT5PR8401MB1169D656C8B5E121752FC0F8AB120@AT5PR8401MB1169.NAMPRD84.PROD.OUTLOOK.COM
[3]: https://lkml.org/lkml/2018/10/12/309
[dan.j.williams@intel.com: fix shuffle enable]
Link: http://lkml.kernel.org/r/154943713038.3858443.4125180191382062871.stgit@dwillia2-desk3.amr.corp.intel.com
[cai@lca.pw: fix SHUFFLE_PAGE_ALLOCATOR help texts]
Link: http://lkml.kernel.org/r/20190425201300.75650-1-cai@lca.pw
Link: http://lkml.kernel.org/r/154899811738.3165233.12325692939590944259.stgit@dwillia2-desk3.amr.corp.intel.com
Signed-off-by: Dan Williams <dan.j.williams@intel.com>
Signed-off-by: Qian Cai <cai@lca.pw>
Reviewed-by: Kees Cook <keescook@chromium.org>
Acked-by: Michal Hocko <mhocko@suse.com>
Cc: Dave Hansen <dave.hansen@linux.intel.com>
Cc: Keith Busch <keith.busch@intel.com>
Cc: Robert Elliott <elliott@hpe.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-05-15 01:41:28 +03:00
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// SPDX-License-Identifier: GPL-2.0
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// Copyright(c) 2018 Intel Corporation. All rights reserved.
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#ifndef _MM_SHUFFLE_H
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#define _MM_SHUFFLE_H
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#include <linux/jump_label.h>
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/*
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* SHUFFLE_ENABLE is called from the command line enabling path, or by
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* platform-firmware enabling that indicates the presence of a
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* direct-mapped memory-side-cache. SHUFFLE_FORCE_DISABLE is called from
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* the command line path and overrides any previous or future
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* SHUFFLE_ENABLE.
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*/
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enum mm_shuffle_ctl {
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SHUFFLE_ENABLE,
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SHUFFLE_FORCE_DISABLE,
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};
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#define SHUFFLE_ORDER (MAX_ORDER-1)
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#ifdef CONFIG_SHUFFLE_PAGE_ALLOCATOR
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DECLARE_STATIC_KEY_FALSE(page_alloc_shuffle_key);
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extern void page_alloc_shuffle(enum mm_shuffle_ctl ctl);
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extern void __shuffle_free_memory(pg_data_t *pgdat);
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static inline void shuffle_free_memory(pg_data_t *pgdat)
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{
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if (!static_branch_unlikely(&page_alloc_shuffle_key))
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return;
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__shuffle_free_memory(pgdat);
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}
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extern void __shuffle_zone(struct zone *z);
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static inline void shuffle_zone(struct zone *z)
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{
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if (!static_branch_unlikely(&page_alloc_shuffle_key))
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return;
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__shuffle_zone(z);
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}
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2019-05-15 01:41:35 +03:00
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static inline bool is_shuffle_order(int order)
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{
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if (!static_branch_unlikely(&page_alloc_shuffle_key))
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return false;
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return order >= SHUFFLE_ORDER;
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}
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mm: shuffle initial free memory to improve memory-side-cache utilization
Patch series "mm: Randomize free memory", v10.
This patch (of 3):
Randomization of the page allocator improves the average utilization of
a direct-mapped memory-side-cache. Memory side caching is a platform
capability that Linux has been previously exposed to in HPC
(high-performance computing) environments on specialty platforms. In
that instance it was a smaller pool of high-bandwidth-memory relative to
higher-capacity / lower-bandwidth DRAM. Now, this capability is going
to be found on general purpose server platforms where DRAM is a cache in
front of higher latency persistent memory [1].
Robert offered an explanation of the state of the art of Linux
interactions with memory-side-caches [2], and I copy it here:
It's been a problem in the HPC space:
http://www.nersc.gov/research-and-development/knl-cache-mode-performance-coe/
A kernel module called zonesort is available to try to help:
https://software.intel.com/en-us/articles/xeon-phi-software
and this abandoned patch series proposed that for the kernel:
https://lkml.kernel.org/r/20170823100205.17311-1-lukasz.daniluk@intel.com
Dan's patch series doesn't attempt to ensure buffers won't conflict, but
also reduces the chance that the buffers will. This will make performance
more consistent, albeit slower than "optimal" (which is near impossible
to attain in a general-purpose kernel). That's better than forcing
users to deploy remedies like:
"To eliminate this gradual degradation, we have added a Stream
measurement to the Node Health Check that follows each job;
nodes are rebooted whenever their measured memory bandwidth
falls below 300 GB/s."
A replacement for zonesort was merged upstream in commit cc9aec03e58f
("x86/numa_emulation: Introduce uniform split capability"). With this
numa_emulation capability, memory can be split into cache sized
("near-memory" sized) numa nodes. A bind operation to such a node, and
disabling workloads on other nodes, enables full cache performance.
However, once the workload exceeds the cache size then cache conflicts
are unavoidable. While HPC environments might be able to tolerate
time-scheduling of cache sized workloads, for general purpose server
platforms, the oversubscribed cache case will be the common case.
The worst case scenario is that a server system owner benchmarks a
workload at boot with an un-contended cache only to see that performance
degrade over time, even below the average cache performance due to
excessive conflicts. Randomization clips the peaks and fills in the
valleys of cache utilization to yield steady average performance.
Here are some performance impact details of the patches:
1/ An Intel internal synthetic memory bandwidth measurement tool, saw a
3X speedup in a contrived case that tries to force cache conflicts.
The contrived cased used the numa_emulation capability to force an
instance of the benchmark to be run in two of the near-memory sized
numa nodes. If both instances were placed on the same emulated they
would fit and cause zero conflicts. While on separate emulated nodes
without randomization they underutilized the cache and conflicted
unnecessarily due to the in-order allocation per node.
2/ A well known Java server application benchmark was run with a heap
size that exceeded cache size by 3X. The cache conflict rate was 8%
for the first run and degraded to 21% after page allocator aging. With
randomization enabled the rate levelled out at 11%.
3/ A MongoDB workload did not observe measurable difference in
cache-conflict rates, but the overall throughput dropped by 7% with
randomization in one case.
4/ Mel Gorman ran his suite of performance workloads with randomization
enabled on platforms without a memory-side-cache and saw a mix of some
improvements and some losses [3].
While there is potentially significant improvement for applications that
depend on low latency access across a wide working-set, the performance
may be negligible to negative for other workloads. For this reason the
shuffle capability defaults to off unless a direct-mapped
memory-side-cache is detected. Even then, the page_alloc.shuffle=0
parameter can be specified to disable the randomization on those systems.
Outside of memory-side-cache utilization concerns there is potentially
security benefit from randomization. Some data exfiltration and
return-oriented-programming attacks rely on the ability to infer the
location of sensitive data objects. The kernel page allocator, especially
early in system boot, has predictable first-in-first out behavior for
physical pages. Pages are freed in physical address order when first
onlined.
Quoting Kees:
"While we already have a base-address randomization
(CONFIG_RANDOMIZE_MEMORY), attacks against the same hardware and
memory layouts would certainly be using the predictability of
allocation ordering (i.e. for attacks where the base address isn't
important: only the relative positions between allocated memory).
This is common in lots of heap-style attacks. They try to gain
control over ordering by spraying allocations, etc.
I'd really like to see this because it gives us something similar
to CONFIG_SLAB_FREELIST_RANDOM but for the page allocator."
While SLAB_FREELIST_RANDOM reduces the predictability of some local slab
caches it leaves vast bulk of memory to be predictably in order allocated.
However, it should be noted, the concrete security benefits are hard to
quantify, and no known CVE is mitigated by this randomization.
Introduce shuffle_free_memory(), and its helper shuffle_zone(), to perform
a Fisher-Yates shuffle of the page allocator 'free_area' lists when they
are initially populated with free memory at boot and at hotplug time. Do
this based on either the presence of a page_alloc.shuffle=Y command line
parameter, or autodetection of a memory-side-cache (to be added in a
follow-on patch).
The shuffling is done in terms of CONFIG_SHUFFLE_PAGE_ORDER sized free
pages where the default CONFIG_SHUFFLE_PAGE_ORDER is MAX_ORDER-1 i.e. 10,
4MB this trades off randomization granularity for time spent shuffling.
MAX_ORDER-1 was chosen to be minimally invasive to the page allocator
while still showing memory-side cache behavior improvements, and the
expectation that the security implications of finer granularity
randomization is mitigated by CONFIG_SLAB_FREELIST_RANDOM. The
performance impact of the shuffling appears to be in the noise compared to
other memory initialization work.
This initial randomization can be undone over time so a follow-on patch is
introduced to inject entropy on page free decisions. It is reasonable to
ask if the page free entropy is sufficient, but it is not enough due to
the in-order initial freeing of pages. At the start of that process
putting page1 in front or behind page0 still keeps them close together,
page2 is still near page1 and has a high chance of being adjacent. As
more pages are added ordering diversity improves, but there is still high
page locality for the low address pages and this leads to no significant
impact to the cache conflict rate.
[1]: https://itpeernetwork.intel.com/intel-optane-dc-persistent-memory-operating-modes/
[2]: https://lkml.kernel.org/r/AT5PR8401MB1169D656C8B5E121752FC0F8AB120@AT5PR8401MB1169.NAMPRD84.PROD.OUTLOOK.COM
[3]: https://lkml.org/lkml/2018/10/12/309
[dan.j.williams@intel.com: fix shuffle enable]
Link: http://lkml.kernel.org/r/154943713038.3858443.4125180191382062871.stgit@dwillia2-desk3.amr.corp.intel.com
[cai@lca.pw: fix SHUFFLE_PAGE_ALLOCATOR help texts]
Link: http://lkml.kernel.org/r/20190425201300.75650-1-cai@lca.pw
Link: http://lkml.kernel.org/r/154899811738.3165233.12325692939590944259.stgit@dwillia2-desk3.amr.corp.intel.com
Signed-off-by: Dan Williams <dan.j.williams@intel.com>
Signed-off-by: Qian Cai <cai@lca.pw>
Reviewed-by: Kees Cook <keescook@chromium.org>
Acked-by: Michal Hocko <mhocko@suse.com>
Cc: Dave Hansen <dave.hansen@linux.intel.com>
Cc: Keith Busch <keith.busch@intel.com>
Cc: Robert Elliott <elliott@hpe.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-05-15 01:41:28 +03:00
|
|
|
#else
|
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|
|
|
static inline void shuffle_free_memory(pg_data_t *pgdat)
|
|
|
|
|
{
|
|
|
|
|
}
|
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|
|
|
|
|
|
|
static inline void shuffle_zone(struct zone *z)
|
|
|
|
|
{
|
|
|
|
|
}
|
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|
|
|
|
|
|
|
|
static inline void page_alloc_shuffle(enum mm_shuffle_ctl ctl)
|
|
|
|
|
{
|
|
|
|
|
}
|
2019-05-15 01:41:35 +03:00
|
|
|
|
|
|
|
|
static inline bool is_shuffle_order(int order)
|
|
|
|
|
{
|
|
|
|
|
return false;
|
|
|
|
|
}
|
mm: shuffle initial free memory to improve memory-side-cache utilization
Patch series "mm: Randomize free memory", v10.
This patch (of 3):
Randomization of the page allocator improves the average utilization of
a direct-mapped memory-side-cache. Memory side caching is a platform
capability that Linux has been previously exposed to in HPC
(high-performance computing) environments on specialty platforms. In
that instance it was a smaller pool of high-bandwidth-memory relative to
higher-capacity / lower-bandwidth DRAM. Now, this capability is going
to be found on general purpose server platforms where DRAM is a cache in
front of higher latency persistent memory [1].
Robert offered an explanation of the state of the art of Linux
interactions with memory-side-caches [2], and I copy it here:
It's been a problem in the HPC space:
http://www.nersc.gov/research-and-development/knl-cache-mode-performance-coe/
A kernel module called zonesort is available to try to help:
https://software.intel.com/en-us/articles/xeon-phi-software
and this abandoned patch series proposed that for the kernel:
https://lkml.kernel.org/r/20170823100205.17311-1-lukasz.daniluk@intel.com
Dan's patch series doesn't attempt to ensure buffers won't conflict, but
also reduces the chance that the buffers will. This will make performance
more consistent, albeit slower than "optimal" (which is near impossible
to attain in a general-purpose kernel). That's better than forcing
users to deploy remedies like:
"To eliminate this gradual degradation, we have added a Stream
measurement to the Node Health Check that follows each job;
nodes are rebooted whenever their measured memory bandwidth
falls below 300 GB/s."
A replacement for zonesort was merged upstream in commit cc9aec03e58f
("x86/numa_emulation: Introduce uniform split capability"). With this
numa_emulation capability, memory can be split into cache sized
("near-memory" sized) numa nodes. A bind operation to such a node, and
disabling workloads on other nodes, enables full cache performance.
However, once the workload exceeds the cache size then cache conflicts
are unavoidable. While HPC environments might be able to tolerate
time-scheduling of cache sized workloads, for general purpose server
platforms, the oversubscribed cache case will be the common case.
The worst case scenario is that a server system owner benchmarks a
workload at boot with an un-contended cache only to see that performance
degrade over time, even below the average cache performance due to
excessive conflicts. Randomization clips the peaks and fills in the
valleys of cache utilization to yield steady average performance.
Here are some performance impact details of the patches:
1/ An Intel internal synthetic memory bandwidth measurement tool, saw a
3X speedup in a contrived case that tries to force cache conflicts.
The contrived cased used the numa_emulation capability to force an
instance of the benchmark to be run in two of the near-memory sized
numa nodes. If both instances were placed on the same emulated they
would fit and cause zero conflicts. While on separate emulated nodes
without randomization they underutilized the cache and conflicted
unnecessarily due to the in-order allocation per node.
2/ A well known Java server application benchmark was run with a heap
size that exceeded cache size by 3X. The cache conflict rate was 8%
for the first run and degraded to 21% after page allocator aging. With
randomization enabled the rate levelled out at 11%.
3/ A MongoDB workload did not observe measurable difference in
cache-conflict rates, but the overall throughput dropped by 7% with
randomization in one case.
4/ Mel Gorman ran his suite of performance workloads with randomization
enabled on platforms without a memory-side-cache and saw a mix of some
improvements and some losses [3].
While there is potentially significant improvement for applications that
depend on low latency access across a wide working-set, the performance
may be negligible to negative for other workloads. For this reason the
shuffle capability defaults to off unless a direct-mapped
memory-side-cache is detected. Even then, the page_alloc.shuffle=0
parameter can be specified to disable the randomization on those systems.
Outside of memory-side-cache utilization concerns there is potentially
security benefit from randomization. Some data exfiltration and
return-oriented-programming attacks rely on the ability to infer the
location of sensitive data objects. The kernel page allocator, especially
early in system boot, has predictable first-in-first out behavior for
physical pages. Pages are freed in physical address order when first
onlined.
Quoting Kees:
"While we already have a base-address randomization
(CONFIG_RANDOMIZE_MEMORY), attacks against the same hardware and
memory layouts would certainly be using the predictability of
allocation ordering (i.e. for attacks where the base address isn't
important: only the relative positions between allocated memory).
This is common in lots of heap-style attacks. They try to gain
control over ordering by spraying allocations, etc.
I'd really like to see this because it gives us something similar
to CONFIG_SLAB_FREELIST_RANDOM but for the page allocator."
While SLAB_FREELIST_RANDOM reduces the predictability of some local slab
caches it leaves vast bulk of memory to be predictably in order allocated.
However, it should be noted, the concrete security benefits are hard to
quantify, and no known CVE is mitigated by this randomization.
Introduce shuffle_free_memory(), and its helper shuffle_zone(), to perform
a Fisher-Yates shuffle of the page allocator 'free_area' lists when they
are initially populated with free memory at boot and at hotplug time. Do
this based on either the presence of a page_alloc.shuffle=Y command line
parameter, or autodetection of a memory-side-cache (to be added in a
follow-on patch).
The shuffling is done in terms of CONFIG_SHUFFLE_PAGE_ORDER sized free
pages where the default CONFIG_SHUFFLE_PAGE_ORDER is MAX_ORDER-1 i.e. 10,
4MB this trades off randomization granularity for time spent shuffling.
MAX_ORDER-1 was chosen to be minimally invasive to the page allocator
while still showing memory-side cache behavior improvements, and the
expectation that the security implications of finer granularity
randomization is mitigated by CONFIG_SLAB_FREELIST_RANDOM. The
performance impact of the shuffling appears to be in the noise compared to
other memory initialization work.
This initial randomization can be undone over time so a follow-on patch is
introduced to inject entropy on page free decisions. It is reasonable to
ask if the page free entropy is sufficient, but it is not enough due to
the in-order initial freeing of pages. At the start of that process
putting page1 in front or behind page0 still keeps them close together,
page2 is still near page1 and has a high chance of being adjacent. As
more pages are added ordering diversity improves, but there is still high
page locality for the low address pages and this leads to no significant
impact to the cache conflict rate.
[1]: https://itpeernetwork.intel.com/intel-optane-dc-persistent-memory-operating-modes/
[2]: https://lkml.kernel.org/r/AT5PR8401MB1169D656C8B5E121752FC0F8AB120@AT5PR8401MB1169.NAMPRD84.PROD.OUTLOOK.COM
[3]: https://lkml.org/lkml/2018/10/12/309
[dan.j.williams@intel.com: fix shuffle enable]
Link: http://lkml.kernel.org/r/154943713038.3858443.4125180191382062871.stgit@dwillia2-desk3.amr.corp.intel.com
[cai@lca.pw: fix SHUFFLE_PAGE_ALLOCATOR help texts]
Link: http://lkml.kernel.org/r/20190425201300.75650-1-cai@lca.pw
Link: http://lkml.kernel.org/r/154899811738.3165233.12325692939590944259.stgit@dwillia2-desk3.amr.corp.intel.com
Signed-off-by: Dan Williams <dan.j.williams@intel.com>
Signed-off-by: Qian Cai <cai@lca.pw>
Reviewed-by: Kees Cook <keescook@chromium.org>
Acked-by: Michal Hocko <mhocko@suse.com>
Cc: Dave Hansen <dave.hansen@linux.intel.com>
Cc: Keith Busch <keith.busch@intel.com>
Cc: Robert Elliott <elliott@hpe.com>
Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
2019-05-15 01:41:28 +03:00
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#endif
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#endif /* _MM_SHUFFLE_H */
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