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[RFC,v5,0/7] Implement Data Access Monitoring-based Memory Operation Schemes

Message ID 20200330115042.17431-1-sjpark@amazon.com (mailing list archive)
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Series Implement Data Access Monitoring-based Memory Operation Schemes | expand

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SeongJae Park March 30, 2020, 11:50 a.m. UTC
From: SeongJae Park <sjpark@amazon.de>

DAMON[1] can be used as a primitive for data access awared memory management
optimizations.  That said, users who want such optimizations should run DAMON,
read the monitoring results, analyze it, plan a new memory management scheme,
and apply the new scheme by themselves.  Such efforts will be inevitable for
some complicated optimizations.

However, in many other cases, the users could simply want the system to apply a
memory management action to a memory region of a specific size having a
specific access frequency for a specific time.  For example, "page out a memory
region larger than 100 MiB keeping only rare accesses more than 2 minutes", or
"Do not use THP for a memory region larger than 2 MiB rarely accessed for more
than 1 seconds".

This RFC patchset makes DAMON to handle such data access monitoring-based
operation schemes.  With this change, users can do the data access awared
optimizations by simply specifying their schemes to DAMON.


Evaluations
===========

Setup
-----

On my personal QEMU/KVM based virtual machine on an Intel i7 host machine
running Ubuntu 18.04, I measure runtime and consumed system memory while
running various realistic workloads with several configurations.  I use 13 and
12 workloads in PARSEC3[3] and SPLASH-2X[4] benchmark suites, respectively.  I
personally use another wrapper scripts[5] for setup and run of the workloads.
On top of this patchset, we also applied the DAMON-based operation schemes
patchset[6] for this evaluation.

Measurement
~~~~~~~~~~~

For the measurement of the amount of consumed memory in system global scope, I
drop caches before starting each of the workloads and monitor 'MemFree' in the
'/proc/meminfo' file.  To make results more stable, I repeat the runs 5 times
and average results.  You can get stdev, min, and max of the numbers among the
repeated runs in appendix below.

Configurations
~~~~~~~~~~~~~~

The configurations I use are as below.

orig: Linux v5.5 with 'madvise' THP policy
rec: 'orig' plus DAMON running with record feature
thp: same with 'orig', but use 'always' THP policy
ethp: 'orig' plus a DAMON operation scheme[6], 'efficient THP'
prcl: 'orig' plus a DAMON operation scheme, 'proactive reclaim[7]'

I use 'rec' for measurement of DAMON overheads to target workloads and system
memory.  The remaining configs including 'thp', 'ethp', and 'prcl' are for
measurement of DAMON monitoring accuracy.

'ethp' and 'prcl' is simple DAMON-based operation schemes developed for
proof of concepts of DAMON.  'ethp' reduces memory space waste of THP by using
DAMON for decision of promotions and demotion for huge pages, while 'prcl' is
as similar as the original work.  Those are implemented as below:

# format: <min/max size> <min/max frequency (0-100)> <min/max age> <action>
# ethp: Use huge pages if a region >2MB shows >5% access rate, use regular
# pages if a region >2MB shows <5% access rate for >1 second
2M null    5 null    null null    hugepage
2M null    null 5    1s null      nohugepage

# prcl: If a region >4KB shows <5% access rate for >5 seconds, page out.
4K null    null 5    5s null      pageout

Note that both 'ethp' and 'prcl' are designed with my only straightforward
intuition, because those are for only proof of concepts and monitoring accuracy
of DAMON.  In other words, those are not for production.  For production use,
those should be tuned more.


[1] "Redis latency problems troubleshooting", https://redis.io/topics/latency
[2] "Disable Transparent Huge Pages (THP)",
    https://docs.mongodb.com/manual/tutorial/transparent-huge-pages/
[3] "The PARSEC Becnhmark Suite", https://parsec.cs.princeton.edu/index.htm
[4] "SPLASH-2x", https://parsec.cs.princeton.edu/parsec3-doc.htm#splash2x
[5] "parsec3_on_ubuntu", https://github.com/sjp38/parsec3_on_ubuntu
[6] "[RFC v4 0/7] Implement Data Access Monitoring-based Memory Operation
    Schemes",
    https://lore.kernel.org/linux-mm/20200303121406.20954-1-sjpark@amazon.com/
[7] "Proactively reclaiming idle memory", https://lwn.net/Articles/787611/


Results
-------

Below two tables show the measurement results.  The runtimes are in seconds
while the memory usages are in KiB.  Each configurations except 'orig' shows
its overhead relative to 'orig' in percent within parenthesises.

runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
parsec3/blackscholes    107.594  107.956  (0.34)     106.750  (-0.78)    107.672  (0.07)     111.916  (4.02)    
parsec3/bodytrack       79.230   79.368   (0.17)     78.908   (-0.41)    79.705   (0.60)     80.423   (1.50)    
parsec3/canneal         142.831  143.810  (0.69)     123.530  (-13.51)   133.778  (-6.34)    144.998  (1.52)    
parsec3/dedup           11.986   11.959   (-0.23)    11.762   (-1.87)    12.028   (0.35)     13.313   (11.07)   
parsec3/facesim         210.125  209.007  (-0.53)    205.226  (-2.33)    207.766  (-1.12)    209.815  (-0.15)   
parsec3/ferret          191.601  191.177  (-0.22)    190.420  (-0.62)    191.775  (0.09)     192.638  (0.54)    
parsec3/fluidanimate    212.735  212.970  (0.11)     209.151  (-1.68)    211.904  (-0.39)    218.573  (2.74)    
parsec3/freqmine        291.225  290.873  (-0.12)    289.258  (-0.68)    289.884  (-0.46)    298.373  (2.45)    
parsec3/raytrace        118.289  119.586  (1.10)     119.045  (0.64)     119.064  (0.66)     137.919  (16.60)   
parsec3/streamcluster   323.565  328.168  (1.42)     279.565  (-13.60)   287.452  (-11.16)   333.244  (2.99)    
parsec3/swaptions       155.140  155.473  (0.21)     153.816  (-0.85)    156.423  (0.83)     156.237  (0.71)    
parsec3/vips            58.979   59.311   (0.56)     58.733   (-0.42)    59.005   (0.04)     61.062   (3.53)    
parsec3/x264            70.539   68.413   (-3.01)    64.760   (-8.19)    67.180   (-4.76)    68.103   (-3.45)   
splash2x/barnes         80.414   81.751   (1.66)     73.585   (-8.49)    80.232   (-0.23)    115.753  (43.95)   
splash2x/fft            33.902   34.111   (0.62)     24.228   (-28.53)   29.926   (-11.73)   44.438   (31.08)   
splash2x/lu_cb          85.556   86.001   (0.52)     84.538   (-1.19)    86.000   (0.52)     91.447   (6.89)    
splash2x/lu_ncb         93.399   93.652   (0.27)     90.463   (-3.14)    94.008   (0.65)     93.901   (0.54)    
splash2x/ocean_cp       45.253   45.191   (-0.14)    43.049   (-4.87)    44.022   (-2.72)    46.588   (2.95)    
splash2x/ocean_ncp      86.927   87.065   (0.16)     50.747   (-41.62)   86.855   (-0.08)    199.553  (129.57)  
splash2x/radiosity      91.433   91.511   (0.09)     90.626   (-0.88)    91.865   (0.47)     104.524  (14.32)   
splash2x/radix          31.923   32.023   (0.31)     25.194   (-21.08)   32.035   (0.35)     39.231   (22.89)   
splash2x/raytrace       84.367   84.677   (0.37)     82.417   (-2.31)    83.505   (-1.02)    84.857   (0.58)    
splash2x/volrend        87.499   87.495   (-0.00)    86.775   (-0.83)    87.311   (-0.21)    87.511   (0.01)    
splash2x/water_nsquared 236.397  236.759  (0.15)     219.902  (-6.98)    224.228  (-5.15)    238.562  (0.92)    
splash2x/water_spatial  89.646   89.767   (0.14)     89.735   (0.10)     90.347   (0.78)     103.585  (15.55)   
total                   3020.570 3028.080 (0.25)     2852.190 (-5.57)    2953.960 (-2.21)    3276.550 (8.47)    


memused.avg             orig         rec          (overhead) thp          (overhead) ethp         (overhead) prcl         (overhead)
parsec3/blackscholes    1785916.600  1834201.400  (2.70)     1826249.200  (2.26)     1828079.200  (2.36)     1712210.600  (-4.13)   
parsec3/bodytrack       1415049.400  1434317.600  (1.36)     1423715.000  (0.61)     1430392.600  (1.08)     1435136.000  (1.42)    
parsec3/canneal         1043489.800  1058617.600  (1.45)     1040484.600  (-0.29)    1048664.800  (0.50)     1050280.000  (0.65)    
parsec3/dedup           2414453.200  2458493.200  (1.82)     2411379.400  (-0.13)    2400516.000  (-0.58)    2461120.800  (1.93)    
parsec3/facesim         541597.200   550097.400   (1.57)     544364.600   (0.51)     553240.000   (2.15)     552316.400   (1.98)    
parsec3/ferret          317986.600   332346.000   (4.52)     320218.000   (0.70)     331085.000   (4.12)     330895.200   (4.06)    
parsec3/fluidanimate    576183.400   585442.000   (1.61)     577780.200   (0.28)     587703.400   (2.00)     506501.000   (-12.09)  
parsec3/freqmine        990869.200   997817.000   (0.70)     990350.400   (-0.05)    997669.000   (0.69)     763325.800   (-22.96)  
parsec3/raytrace        1748370.800  1757109.200  (0.50)     1746153.800  (-0.13)    1757830.400  (0.54)     1581455.800  (-9.55)   
parsec3/streamcluster   121521.800   140452.400   (15.58)    129725.400   (6.75)     132266.000   (8.84)     130558.200   (7.44)    
parsec3/swaptions       15592.400    29018.800    (86.11)    14765.800    (-5.30)    27260.200    (74.83)    26631.600    (70.80)   
parsec3/vips            2957567.600  2967993.800  (0.35)     2956623.200  (-0.03)    2973062.600  (0.52)     2951402.000  (-0.21)   
parsec3/x264            3169012.400  3175048.800  (0.19)     3190345.400  (0.67)     3189353.000  (0.64)     3172924.200  (0.12)    
splash2x/barnes         1209066.000  1213125.400  (0.34)     1217261.400  (0.68)     1209661.600  (0.05)     921041.800   (-23.82)  
splash2x/fft            9359313.200  9195213.000  (-1.75)    9377562.400  (0.19)     9050957.600  (-3.29)    9517977.000  (1.70)    
splash2x/lu_cb          514966.200   522939.400   (1.55)     520870.400   (1.15)     522635.000   (1.49)     329933.600   (-35.93)  
splash2x/lu_ncb         514180.400   525974.800   (2.29)     521420.200   (1.41)     521063.600   (1.34)     523557.000   (1.82)    
splash2x/ocean_cp       3346493.400  3288078.000  (-1.75)    3382253.800  (1.07)     3289477.600  (-1.70)    3260810.400  (-2.56)   
splash2x/ocean_ncp      3909966.400  3882968.800  (-0.69)    7037196.000  (79.98)    4046363.400  (3.49)     3471452.400  (-11.22)  
splash2x/radiosity      1471119.400  1470626.800  (-0.03)    1482604.200  (0.78)     1472718.400  (0.11)     546893.600   (-62.82)  
splash2x/radix          1748360.800  1729163.400  (-1.10)    1371463.200  (-21.56)   1701993.600  (-2.65)    1817519.600  (3.96)    
splash2x/raytrace       46670.000    60172.200    (28.93)    51901.600    (11.21)    60782.600    (30.24)    52644.800    (12.80)   
splash2x/volrend        150666.600   167444.200   (11.14)    151335.200   (0.44)     163345.000   (8.41)     162760.000   (8.03)    
splash2x/water_nsquared 45720.200    59422.400    (29.97)    46031.000    (0.68)     61801.400    (35.17)    62627.000    (36.98)   
splash2x/water_spatial  663052.200   672855.800   (1.48)     665787.600   (0.41)     674696.200   (1.76)     471052.600   (-28.96)  
total                   40077300.000 40108900.000 (0.08)     42997900.000 (7.29)     40032700.000 (-0.11)    37813000.000 (-5.65)   


DAMON Overheads
~~~~~~~~~~~~~~~

In total, DAMON recording feature incurs 0.25% runtime overhead (up to 1.66% in
worst case with 'splash2x/barnes') and 0.08% memory space overhead.

For convenience test run of 'rec', I use a Python wrapper.  The wrapper
constantly consumes about 10-15MB of memory.  This becomes high memory overhead
if the target workload has small memory footprint.  In detail, 16%, 86%, 29%,
11%, and 30% overheads shown for parsec3/streamcluster (125 MiB),
parsec3/swaptions (15 MiB), splash2x/raytrace (45 MiB), splash2x/volrend (151
MiB), and splash2x/water_nsquared (46 MiB)).  Nonetheless, the overheads are
not from DAMON, but from the wrapper, and thus should be ignored.  This fake
memory overhead continues in 'ethp' and 'prcl', as those configurations are
also using the Python wrapper.


Efficient THP
~~~~~~~~~~~~~

THP 'always' enabled policy achieves 5.57% speedup but incurs 7.29% memory
overhead.  It achieves 41.62% speedup in best case, but 79.98% memory overhead
in worst case.  Interestingly, both the best and worst case are with
'splash2x/ocean_ncp').

The 2-lines implementation of data access monitoring based THP version ('ethp')
shows 2.21% speedup and -0.11% memory overhead.  In other words, 'ethp' removes
100% of THP memory waste while preserving 39.67% of THP speedup in total.


Proactive Reclamation
~~~~~~~~~~~~~~~~~~~~

As same to the original work, I use 'zram' swap device for this configuration.

In total, our 1 line implementation of Proactive Reclamation, 'prcl', incurred
8.47% runtime overhead in total while achieving 5.65% system memory usage
reduction.

Nonetheless, as the memory usage is calculated with 'MemFree' in
'/proc/meminfo', it contains the SwapCached pages.  As the swapcached pages can
be easily evicted, I also measured the residential set size of the workloads:

rss.avg                 orig         rec          (overhead) thp          (overhead) ethp         (overhead) prcl         (overhead)
parsec3/blackscholes    592502.000   589764.400   (-0.46)    592132.600   (-0.06)    593702.000   (0.20)     406639.400   (-31.37)  
parsec3/bodytrack       32365.400    32195.000    (-0.53)    32210.800    (-0.48)    32114.600    (-0.77)    21537.600    (-33.45)  
parsec3/canneal         839904.200   840292.200   (0.05)     836866.400   (-0.36)    838263.200   (-0.20)    837895.800   (-0.24)   
parsec3/dedup           1208337.200  1218465.600  (0.84)     1233278.600  (2.06)     1200490.200  (-0.65)    882911.400   (-26.93)  
parsec3/facesim         311380.800   311363.600   (-0.01)    315642.600   (1.37)     312573.400   (0.38)     310257.400   (-0.36)   
parsec3/ferret          99514.800    99542.000    (0.03)     100454.200   (0.94)     99879.800    (0.37)     89679.200    (-9.88)   
parsec3/fluidanimate    531760.800   531735.200   (-0.00)    531865.400   (0.02)     531940.800   (0.03)     440781.000   (-17.11)  
parsec3/freqmine        552455.400   552882.600   (0.08)     555793.600   (0.60)     553019.800   (0.10)     58067.000    (-89.49)  
parsec3/raytrace        894798.400   894953.400   (0.02)     892223.400   (-0.29)    893012.400   (-0.20)    315259.800   (-64.77)  
parsec3/streamcluster   110780.400   110856.800   (0.07)     110954.000   (0.16)     111310.800   (0.48)     108066.800   (-2.45)   
parsec3/swaptions       5614.600     5645.600     (0.55)     5553.200     (-1.09)    5552.600     (-1.10)    3251.800     (-42.08)  
parsec3/vips            31942.200    31752.800    (-0.59)    32042.600    (0.31)     32226.600    (0.89)     29012.200    (-9.17)   
parsec3/x264            81770.800    81609.200    (-0.20)    82800.800    (1.26)     82612.200    (1.03)     81805.800    (0.04)    
splash2x/barnes         1216515.600  1217113.800  (0.05)     1225605.600  (0.75)     1217325.000  (0.07)     540108.400   (-55.60)  
splash2x/fft            9668660.600  9751350.800  (0.86)     9773806.400  (1.09)     9613555.400  (-0.57)    7951241.800  (-17.76)  
splash2x/lu_cb          510368.800   510095.800   (-0.05)    514350.600   (0.78)     510276.000   (-0.02)    311584.800   (-38.95)  
splash2x/lu_ncb         509904.800   510001.600   (0.02)     513847.000   (0.77)     510073.400   (0.03)     509905.600   (0.00)    
splash2x/ocean_cp       3389550.600  3404466.000  (0.44)     3443363.600  (1.59)     3410388.000  (0.61)     3330608.600  (-1.74)   
splash2x/ocean_ncp      3923723.200  3911148.200  (-0.32)    7175800.400  (82.88)    4104482.400  (4.61)     2030525.000  (-48.25)  
splash2x/radiosity      1472994.600  1475946.400  (0.20)     1485636.800  (0.86)     1476193.000  (0.22)     262161.400   (-82.20)  
splash2x/radix          1750329.800  1765697.000  (0.88)     1413304.000  (-19.25)   1754154.400  (0.22)     1516142.600  (-13.38)  
splash2x/raytrace       23149.600    23208.000    (0.25)     28574.400    (23.43)    26694.600    (15.31)    16257.800    (-29.77)  
splash2x/volrend        43968.800    43919.000    (-0.11)    44087.600    (0.27)     44224.000    (0.58)     32484.400    (-26.12)  
splash2x/water_nsquared 29348.000    29338.400    (-0.03)    29604.600    (0.87)     29779.400    (1.47)     23644.800    (-19.43)  
splash2x/water_spatial  655263.600   655097.800   (-0.03)    655199.200   (-0.01)    656282.400   (0.16)     379816.800   (-42.04)  
total                   28486900.000 28598400.000 (0.39)     31625000.000 (11.02)    28640100.000 (0.54)     20489600.000 (-28.07)  

In total, 28.07% of residential sets were reduced.

With parsec3/freqmine, 'prcl' reduced 22.96% of system memory usage and 89.49%
of residential sets while incurring only 2.45% runtime overhead.


Sequence Of Patches
===================

The patches are based on the v5.6 plus v7 DAMON patchset[1] and Minchan's
``do_madvise()`` patch[2].  Minchan's patch was necessary for reuse of
``madvise()`` code in DAMON.  You can also clone the complete git tree:

    $ git clone git://github.com/sjp38/linux -b damos/rfc/v5

The web is also available:
https://github.com/sjp38/linux/releases/tag/damos/rfc/v5


[1] https://lore.kernel.org/linux-mm/20200318112722.30143-1-sjpark@amazon.com/
[2] https://lore.kernel.org/linux-mm/20200302193630.68771-2-minchan@kernel.org/

The first patch allows DAMON to reuse ``madvise()`` code for the actions.  The
second patch accounts age of each region.  The third patch implements the
handling of the schemes in DAMON and exports a kernel space programming
interface for it.  The fourth patch implements a debugfs interface for
privileged people and programs.  The fifth and sixth patches each adds
kunittests and selftests for these changes, and finally the seventhe patch
modifies the user space tool for DAMON to support description and applying of
schemes in human freiendly way.


Patch History
=============

Changes from RFC v4
(https://lore.kernel.org/linux-mm/20200303121406.20954-1-sjpark@amazon.com/)
 - Handle CONFIG_ADVISE_SYSCALL
 - Clean up code (Jonathan Cameron)
 - Update test results
 - Rebase on v5.6 + DAMON v7

Changes from RFC v3
(https://lore.kernel.org/linux-mm/20200225102300.23895-1-sjpark@amazon.com/)
 - Add Reviewed-by from Brendan Higgins
 - Code cleanup: Modularize madvise() call
 - Fix a trivial bug in the wrapper python script
 - Add more stable and detailed evaluation results with updated ETHP scheme

Changes from RFC v2
(https://lore.kernel.org/linux-mm/20200218085309.18346-1-sjpark@amazon.com/)
 - Fix aging mechanism for more better 'old region' selection
 - Add more kunittests and kselftests for this patchset
 - Support more human friedly description and application of 'schemes'

Changes from RFC v1
(https://lore.kernel.org/linux-mm/20200210150921.32482-1-sjpark@amazon.com/)
 - Properly adjust age accounting related properties after splitting, merging,
   and action applying
SeongJae Park (7):
  mm/madvise: Export do_madvise() to external GPL modules
  mm/damon: Account age of target regions
  mm/damon: Implement data access monitoring-based operation schemes
  mm/damon/schemes: Implement a debugfs interface
  mm/damon-test: Add kunit test case for regions age accounting
  mm/damon/selftests: Add 'schemes' debugfs tests
  damon/tools: Support more human friendly 'schemes' control

 include/linux/damon.h                         |  29 ++
 mm/damon-test.h                               |   5 +
 mm/damon.c                                    | 428 +++++++++++++++++-
 mm/madvise.c                                  |   1 +
 tools/damon/_convert_damos.py                 | 125 +++++
 tools/damon/_damon.py                         | 143 ++++++
 tools/damon/damo                              |   7 +
 tools/damon/record.py                         | 135 +-----
 tools/damon/schemes.py                        | 105 +++++
 .../testing/selftests/damon/debugfs_attrs.sh  |  29 ++
 10 files changed, 878 insertions(+), 129 deletions(-)
 create mode 100755 tools/damon/_convert_damos.py
 create mode 100644 tools/damon/_damon.py
 create mode 100644 tools/damon/schemes.py

Comments

Jonathan Cameron March 31, 2020, 3:51 p.m. UTC | #1
On Mon, 30 Mar 2020 13:50:35 +0200
SeongJae Park <sjpark@amazon.com> wrote:

> From: SeongJae Park <sjpark@amazon.de>
> 
> DAMON[1] can be used as a primitive for data access awared memory management
> optimizations.  That said, users who want such optimizations should run DAMON,
> read the monitoring results, analyze it, plan a new memory management scheme,
> and apply the new scheme by themselves.  Such efforts will be inevitable for
> some complicated optimizations.
> 
> However, in many other cases, the users could simply want the system to apply a
> memory management action to a memory region of a specific size having a
> specific access frequency for a specific time.  For example, "page out a memory
> region larger than 100 MiB keeping only rare accesses more than 2 minutes", or
> "Do not use THP for a memory region larger than 2 MiB rarely accessed for more
> than 1 seconds".
> 
> This RFC patchset makes DAMON to handle such data access monitoring-based
> operation schemes.  With this change, users can do the data access awared
> optimizations by simply specifying their schemes to DAMON.


Hi SeongJae,

I'm wondering if I'm misreading the results below or a data handling mixup
occured. See inline.

Thanks,

Jonathan

> 
> 
> Evaluations
> ===========
> 
> Setup
> -----
> 
> On my personal QEMU/KVM based virtual machine on an Intel i7 host machine
> running Ubuntu 18.04, I measure runtime and consumed system memory while
> running various realistic workloads with several configurations.  I use 13 and
> 12 workloads in PARSEC3[3] and SPLASH-2X[4] benchmark suites, respectively.  I
> personally use another wrapper scripts[5] for setup and run of the workloads.
> On top of this patchset, we also applied the DAMON-based operation schemes
> patchset[6] for this evaluation.
> 
> Measurement
> ~~~~~~~~~~~
> 
> For the measurement of the amount of consumed memory in system global scope, I
> drop caches before starting each of the workloads and monitor 'MemFree' in the
> '/proc/meminfo' file.  To make results more stable, I repeat the runs 5 times
> and average results.  You can get stdev, min, and max of the numbers among the
> repeated runs in appendix below.
> 
> Configurations
> ~~~~~~~~~~~~~~
> 
> The configurations I use are as below.
> 
> orig: Linux v5.5 with 'madvise' THP policy
> rec: 'orig' plus DAMON running with record feature
> thp: same with 'orig', but use 'always' THP policy
> ethp: 'orig' plus a DAMON operation scheme[6], 'efficient THP'
> prcl: 'orig' plus a DAMON operation scheme, 'proactive reclaim[7]'
> 
> I use 'rec' for measurement of DAMON overheads to target workloads and system
> memory.  The remaining configs including 'thp', 'ethp', and 'prcl' are for
> measurement of DAMON monitoring accuracy.
> 
> 'ethp' and 'prcl' is simple DAMON-based operation schemes developed for
> proof of concepts of DAMON.  'ethp' reduces memory space waste of THP by using
> DAMON for decision of promotions and demotion for huge pages, while 'prcl' is
> as similar as the original work.  Those are implemented as below:
> 
> # format: <min/max size> <min/max frequency (0-100)> <min/max age> <action>
> # ethp: Use huge pages if a region >2MB shows >5% access rate, use regular
> # pages if a region >2MB shows <5% access rate for >1 second
> 2M null    5 null    null null    hugepage
> 2M null    null 5    1s null      nohugepage
> 
> # prcl: If a region >4KB shows <5% access rate for >5 seconds, page out.
> 4K null    null 5    5s null      pageout
> 
> Note that both 'ethp' and 'prcl' are designed with my only straightforward
> intuition, because those are for only proof of concepts and monitoring accuracy
> of DAMON.  In other words, those are not for production.  For production use,
> those should be tuned more.
> 
> 
> [1] "Redis latency problems troubleshooting", https://redis.io/topics/latency
> [2] "Disable Transparent Huge Pages (THP)",
>     https://docs.mongodb.com/manual/tutorial/transparent-huge-pages/
> [3] "The PARSEC Becnhmark Suite", https://parsec.cs.princeton.edu/index.htm
> [4] "SPLASH-2x", https://parsec.cs.princeton.edu/parsec3-doc.htm#splash2x
> [5] "parsec3_on_ubuntu", https://github.com/sjp38/parsec3_on_ubuntu
> [6] "[RFC v4 0/7] Implement Data Access Monitoring-based Memory Operation
>     Schemes",
>     https://lore.kernel.org/linux-mm/20200303121406.20954-1-sjpark@amazon.com/
> [7] "Proactively reclaiming idle memory", https://lwn.net/Articles/787611/
> 
> 
> Results
> -------
> 
> Below two tables show the measurement results.  The runtimes are in seconds
> while the memory usages are in KiB.  Each configurations except 'orig' shows
> its overhead relative to 'orig' in percent within parenthesises.
> 
> runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
> parsec3/blackscholes    107.594  107.956  (0.34)     106.750  (-0.78)    107.672  (0.07)     111.916  (4.02)    
> parsec3/bodytrack       79.230   79.368   (0.17)     78.908   (-0.41)    79.705   (0.60)     80.423   (1.50)    
> parsec3/canneal         142.831  143.810  (0.69)     123.530  (-13.51)   133.778  (-6.34)    144.998  (1.52)    
> parsec3/dedup           11.986   11.959   (-0.23)    11.762   (-1.87)    12.028   (0.35)     13.313   (11.07)   
> parsec3/facesim         210.125  209.007  (-0.53)    205.226  (-2.33)    207.766  (-1.12)    209.815  (-0.15)   
> parsec3/ferret          191.601  191.177  (-0.22)    190.420  (-0.62)    191.775  (0.09)     192.638  (0.54)    
> parsec3/fluidanimate    212.735  212.970  (0.11)     209.151  (-1.68)    211.904  (-0.39)    218.573  (2.74)    
> parsec3/freqmine        291.225  290.873  (-0.12)    289.258  (-0.68)    289.884  (-0.46)    298.373  (2.45)    
> parsec3/raytrace        118.289  119.586  (1.10)     119.045  (0.64)     119.064  (0.66)     137.919  (16.60)   
> parsec3/streamcluster   323.565  328.168  (1.42)     279.565  (-13.60)   287.452  (-11.16)   333.244  (2.99)    
> parsec3/swaptions       155.140  155.473  (0.21)     153.816  (-0.85)    156.423  (0.83)     156.237  (0.71)    
> parsec3/vips            58.979   59.311   (0.56)     58.733   (-0.42)    59.005   (0.04)     61.062   (3.53)    
> parsec3/x264            70.539   68.413   (-3.01)    64.760   (-8.19)    67.180   (-4.76)    68.103   (-3.45)   
> splash2x/barnes         80.414   81.751   (1.66)     73.585   (-8.49)    80.232   (-0.23)    115.753  (43.95)   
> splash2x/fft            33.902   34.111   (0.62)     24.228   (-28.53)   29.926   (-11.73)   44.438   (31.08)   
> splash2x/lu_cb          85.556   86.001   (0.52)     84.538   (-1.19)    86.000   (0.52)     91.447   (6.89)    
> splash2x/lu_ncb         93.399   93.652   (0.27)     90.463   (-3.14)    94.008   (0.65)     93.901   (0.54)    
> splash2x/ocean_cp       45.253   45.191   (-0.14)    43.049   (-4.87)    44.022   (-2.72)    46.588   (2.95)    
> splash2x/ocean_ncp      86.927   87.065   (0.16)     50.747   (-41.62)   86.855   (-0.08)    199.553  (129.57)  
> splash2x/radiosity      91.433   91.511   (0.09)     90.626   (-0.88)    91.865   (0.47)     104.524  (14.32)   
> splash2x/radix          31.923   32.023   (0.31)     25.194   (-21.08)   32.035   (0.35)     39.231   (22.89)   
> splash2x/raytrace       84.367   84.677   (0.37)     82.417   (-2.31)    83.505   (-1.02)    84.857   (0.58)    
> splash2x/volrend        87.499   87.495   (-0.00)    86.775   (-0.83)    87.311   (-0.21)    87.511   (0.01)    
> splash2x/water_nsquared 236.397  236.759  (0.15)     219.902  (-6.98)    224.228  (-5.15)    238.562  (0.92)    
> splash2x/water_spatial  89.646   89.767   (0.14)     89.735   (0.10)     90.347   (0.78)     103.585  (15.55)   
> total                   3020.570 3028.080 (0.25)     2852.190 (-5.57)    2953.960 (-2.21)    3276.550 (8.47)    
> 
> 
> memused.avg             orig         rec          (overhead) thp          (overhead) ethp         (overhead) prcl         (overhead)
> parsec3/blackscholes    1785916.600  1834201.400  (2.70)     1826249.200  (2.26)     1828079.200  (2.36)     1712210.600  (-4.13)   
> parsec3/bodytrack       1415049.400  1434317.600  (1.36)     1423715.000  (0.61)     1430392.600  (1.08)     1435136.000  (1.42)    
> parsec3/canneal         1043489.800  1058617.600  (1.45)     1040484.600  (-0.29)    1048664.800  (0.50)     1050280.000  (0.65)    
> parsec3/dedup           2414453.200  2458493.200  (1.82)     2411379.400  (-0.13)    2400516.000  (-0.58)    2461120.800  (1.93)    
> parsec3/facesim         541597.200   550097.400   (1.57)     544364.600   (0.51)     553240.000   (2.15)     552316.400   (1.98)    
> parsec3/ferret          317986.600   332346.000   (4.52)     320218.000   (0.70)     331085.000   (4.12)     330895.200   (4.06)    
> parsec3/fluidanimate    576183.400   585442.000   (1.61)     577780.200   (0.28)     587703.400   (2.00)     506501.000   (-12.09)  
> parsec3/freqmine        990869.200   997817.000   (0.70)     990350.400   (-0.05)    997669.000   (0.69)     763325.800   (-22.96)  
> parsec3/raytrace        1748370.800  1757109.200  (0.50)     1746153.800  (-0.13)    1757830.400  (0.54)     1581455.800  (-9.55)   
> parsec3/streamcluster   121521.800   140452.400   (15.58)    129725.400   (6.75)     132266.000   (8.84)     130558.200   (7.44)    
> parsec3/swaptions       15592.400    29018.800    (86.11)    14765.800    (-5.30)    27260.200    (74.83)    26631.600    (70.80)   
> parsec3/vips            2957567.600  2967993.800  (0.35)     2956623.200  (-0.03)    2973062.600  (0.52)     2951402.000  (-0.21)   
> parsec3/x264            3169012.400  3175048.800  (0.19)     3190345.400  (0.67)     3189353.000  (0.64)     3172924.200  (0.12)    
> splash2x/barnes         1209066.000  1213125.400  (0.34)     1217261.400  (0.68)     1209661.600  (0.05)     921041.800   (-23.82)  
> splash2x/fft            9359313.200  9195213.000  (-1.75)    9377562.400  (0.19)     9050957.600  (-3.29)    9517977.000  (1.70)    
> splash2x/lu_cb          514966.200   522939.400   (1.55)     520870.400   (1.15)     522635.000   (1.49)     329933.600   (-35.93)  
> splash2x/lu_ncb         514180.400   525974.800   (2.29)     521420.200   (1.41)     521063.600   (1.34)     523557.000   (1.82)    
> splash2x/ocean_cp       3346493.400  3288078.000  (-1.75)    3382253.800  (1.07)     3289477.600  (-1.70)    3260810.400  (-2.56)   
> splash2x/ocean_ncp      3909966.400  3882968.800  (-0.69)    7037196.000  (79.98)    4046363.400  (3.49)     3471452.400  (-11.22)  
> splash2x/radiosity      1471119.400  1470626.800  (-0.03)    1482604.200  (0.78)     1472718.400  (0.11)     546893.600   (-62.82)  
> splash2x/radix          1748360.800  1729163.400  (-1.10)    1371463.200  (-21.56)   1701993.600  (-2.65)    1817519.600  (3.96)    
> splash2x/raytrace       46670.000    60172.200    (28.93)    51901.600    (11.21)    60782.600    (30.24)    52644.800    (12.80)   
> splash2x/volrend        150666.600   167444.200   (11.14)    151335.200   (0.44)     163345.000   (8.41)     162760.000   (8.03)    
> splash2x/water_nsquared 45720.200    59422.400    (29.97)    46031.000    (0.68)     61801.400    (35.17)    62627.000    (36.98)   
> splash2x/water_spatial  663052.200   672855.800   (1.48)     665787.600   (0.41)     674696.200   (1.76)     471052.600   (-28.96)  
> total                   40077300.000 40108900.000 (0.08)     42997900.000 (7.29)     40032700.000 (-0.11)    37813000.000 (-5.65)   
> 
> 
> DAMON Overheads
> ~~~~~~~~~~~~~~~
> 
> In total, DAMON recording feature incurs 0.25% runtime overhead (up to 1.66% in
> worst case with 'splash2x/barnes') and 0.08% memory space overhead.
> 
> For convenience test run of 'rec', I use a Python wrapper.  The wrapper
> constantly consumes about 10-15MB of memory.  This becomes high memory overhead
> if the target workload has small memory footprint.  In detail, 16%, 86%, 29%,
> 11%, and 30% overheads shown for parsec3/streamcluster (125 MiB),
> parsec3/swaptions (15 MiB), splash2x/raytrace (45 MiB), splash2x/volrend (151
> MiB), and splash2x/water_nsquared (46 MiB)).  Nonetheless, the overheads are
> not from DAMON, but from the wrapper, and thus should be ignored.  This fake
> memory overhead continues in 'ethp' and 'prcl', as those configurations are
> also using the Python wrapper.
> 
> 
> Efficient THP
> ~~~~~~~~~~~~~
> 
> THP 'always' enabled policy achieves 5.57% speedup but incurs 7.29% memory
> overhead.  It achieves 41.62% speedup in best case, but 79.98% memory overhead
> in worst case.  Interestingly, both the best and worst case are with
> 'splash2x/ocean_ncp').

The results above don't seems to support this any more? 

> runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
> splash2x/ocean_ncp      86.927   87.065   (0.16)     50.747   (-41.62)   86.855   (-0.08)    199.553  (129.57) 




> 
> The 2-lines implementation of data access monitoring based THP version ('ethp')
> shows 2.21% speedup and -0.11% memory overhead.  In other words, 'ethp' removes
> 100% of THP memory waste while preserving 39.67% of THP speedup in total.
> 
> 
> Proactive Reclamation
> ~~~~~~~~~~~~~~~~~~~~
> 
> As same to the original work, I use 'zram' swap device for this configuration.
> 
> In total, our 1 line implementation of Proactive Reclamation, 'prcl', incurred
> 8.47% runtime overhead in total while achieving 5.65% system memory usage
> reduction.
> 
> Nonetheless, as the memory usage is calculated with 'MemFree' in
> '/proc/meminfo', it contains the SwapCached pages.  As the swapcached pages can
> be easily evicted, I also measured the residential set size of the workloads:
> 
> rss.avg                 orig         rec          (overhead) thp          (overhead) ethp         (overhead) prcl         (overhead)
> parsec3/blackscholes    592502.000   589764.400   (-0.46)    592132.600   (-0.06)    593702.000   (0.20)     406639.400   (-31.37)  
> parsec3/bodytrack       32365.400    32195.000    (-0.53)    32210.800    (-0.48)    32114.600    (-0.77)    21537.600    (-33.45)  
> parsec3/canneal         839904.200   840292.200   (0.05)     836866.400   (-0.36)    838263.200   (-0.20)    837895.800   (-0.24)   
> parsec3/dedup           1208337.200  1218465.600  (0.84)     1233278.600  (2.06)     1200490.200  (-0.65)    882911.400   (-26.93)  
> parsec3/facesim         311380.800   311363.600   (-0.01)    315642.600   (1.37)     312573.400   (0.38)     310257.400   (-0.36)   
> parsec3/ferret          99514.800    99542.000    (0.03)     100454.200   (0.94)     99879.800    (0.37)     89679.200    (-9.88)   
> parsec3/fluidanimate    531760.800   531735.200   (-0.00)    531865.400   (0.02)     531940.800   (0.03)     440781.000   (-17.11)  
> parsec3/freqmine        552455.400   552882.600   (0.08)     555793.600   (0.60)     553019.800   (0.10)     58067.000    (-89.49)  
> parsec3/raytrace        894798.400   894953.400   (0.02)     892223.400   (-0.29)    893012.400   (-0.20)    315259.800   (-64.77)  
> parsec3/streamcluster   110780.400   110856.800   (0.07)     110954.000   (0.16)     111310.800   (0.48)     108066.800   (-2.45)   
> parsec3/swaptions       5614.600     5645.600     (0.55)     5553.200     (-1.09)    5552.600     (-1.10)    3251.800     (-42.08)  
> parsec3/vips            31942.200    31752.800    (-0.59)    32042.600    (0.31)     32226.600    (0.89)     29012.200    (-9.17)   
> parsec3/x264            81770.800    81609.200    (-0.20)    82800.800    (1.26)     82612.200    (1.03)     81805.800    (0.04)    
> splash2x/barnes         1216515.600  1217113.800  (0.05)     1225605.600  (0.75)     1217325.000  (0.07)     540108.400   (-55.60)  
> splash2x/fft            9668660.600  9751350.800  (0.86)     9773806.400  (1.09)     9613555.400  (-0.57)    7951241.800  (-17.76)  
> splash2x/lu_cb          510368.800   510095.800   (-0.05)    514350.600   (0.78)     510276.000   (-0.02)    311584.800   (-38.95)  
> splash2x/lu_ncb         509904.800   510001.600   (0.02)     513847.000   (0.77)     510073.400   (0.03)     509905.600   (0.00)    
> splash2x/ocean_cp       3389550.600  3404466.000  (0.44)     3443363.600  (1.59)     3410388.000  (0.61)     3330608.600  (-1.74)   
> splash2x/ocean_ncp      3923723.200  3911148.200  (-0.32)    7175800.400  (82.88)    4104482.400  (4.61)     2030525.000  (-48.25)  
> splash2x/radiosity      1472994.600  1475946.400  (0.20)     1485636.800  (0.86)     1476193.000  (0.22)     262161.400   (-82.20)  
> splash2x/radix          1750329.800  1765697.000  (0.88)     1413304.000  (-19.25)   1754154.400  (0.22)     1516142.600  (-13.38)  
> splash2x/raytrace       23149.600    23208.000    (0.25)     28574.400    (23.43)    26694.600    (15.31)    16257.800    (-29.77)  
> splash2x/volrend        43968.800    43919.000    (-0.11)    44087.600    (0.27)     44224.000    (0.58)     32484.400    (-26.12)  
> splash2x/water_nsquared 29348.000    29338.400    (-0.03)    29604.600    (0.87)     29779.400    (1.47)     23644.800    (-19.43)  
> splash2x/water_spatial  655263.600   655097.800   (-0.03)    655199.200   (-0.01)    656282.400   (0.16)     379816.800   (-42.04)  
> total                   28486900.000 28598400.000 (0.39)     31625000.000 (11.02)    28640100.000 (0.54)     20489600.000 (-28.07)  
> 
> In total, 28.07% of residential sets were reduced.
> 
> With parsec3/freqmine, 'prcl' reduced 22.96% of system memory usage and 89.49%
> of residential sets while incurring only 2.45% runtime overhead.
> 
> 
> Sequence Of Patches
> ===================
> 
> The patches are based on the v5.6 plus v7 DAMON patchset[1] and Minchan's
> ``do_madvise()`` patch[2].  Minchan's patch was necessary for reuse of
> ``madvise()`` code in DAMON.  You can also clone the complete git tree:
> 
>     $ git clone git://github.com/sjp38/linux -b damos/rfc/v5
> 
> The web is also available:
> https://github.com/sjp38/linux/releases/tag/damos/rfc/v5
> 
> 
> [1] https://lore.kernel.org/linux-mm/20200318112722.30143-1-sjpark@amazon.com/
> [2] https://lore.kernel.org/linux-mm/20200302193630.68771-2-minchan@kernel.org/
> 
> The first patch allows DAMON to reuse ``madvise()`` code for the actions.  The
> second patch accounts age of each region.  The third patch implements the
> handling of the schemes in DAMON and exports a kernel space programming
> interface for it.  The fourth patch implements a debugfs interface for
> privileged people and programs.  The fifth and sixth patches each adds
> kunittests and selftests for these changes, and finally the seventhe patch
> modifies the user space tool for DAMON to support description and applying of
> schemes in human freiendly way.
> 
> 
> Patch History
> =============
> 
> Changes from RFC v4
> (https://lore.kernel.org/linux-mm/20200303121406.20954-1-sjpark@amazon.com/)
>  - Handle CONFIG_ADVISE_SYSCALL
>  - Clean up code (Jonathan Cameron)
>  - Update test results
>  - Rebase on v5.6 + DAMON v7
> 
> Changes from RFC v3
> (https://lore.kernel.org/linux-mm/20200225102300.23895-1-sjpark@amazon.com/)
>  - Add Reviewed-by from Brendan Higgins
>  - Code cleanup: Modularize madvise() call
>  - Fix a trivial bug in the wrapper python script
>  - Add more stable and detailed evaluation results with updated ETHP scheme
> 
> Changes from RFC v2
> (https://lore.kernel.org/linux-mm/20200218085309.18346-1-sjpark@amazon.com/)
>  - Fix aging mechanism for more better 'old region' selection
>  - Add more kunittests and kselftests for this patchset
>  - Support more human friedly description and application of 'schemes'
> 
> Changes from RFC v1
> (https://lore.kernel.org/linux-mm/20200210150921.32482-1-sjpark@amazon.com/)
>  - Properly adjust age accounting related properties after splitting, merging,
>    and action applying
> SeongJae Park (7):
>   mm/madvise: Export do_madvise() to external GPL modules
>   mm/damon: Account age of target regions
>   mm/damon: Implement data access monitoring-based operation schemes
>   mm/damon/schemes: Implement a debugfs interface
>   mm/damon-test: Add kunit test case for regions age accounting
>   mm/damon/selftests: Add 'schemes' debugfs tests
>   damon/tools: Support more human friendly 'schemes' control
> 
>  include/linux/damon.h                         |  29 ++
>  mm/damon-test.h                               |   5 +
>  mm/damon.c                                    | 428 +++++++++++++++++-
>  mm/madvise.c                                  |   1 +
>  tools/damon/_convert_damos.py                 | 125 +++++
>  tools/damon/_damon.py                         | 143 ++++++
>  tools/damon/damo                              |   7 +
>  tools/damon/record.py                         | 135 +-----
>  tools/damon/schemes.py                        | 105 +++++
>  .../testing/selftests/damon/debugfs_attrs.sh  |  29 ++
>  10 files changed, 878 insertions(+), 129 deletions(-)
>  create mode 100755 tools/damon/_convert_damos.py
>  create mode 100644 tools/damon/_damon.py
>  create mode 100644 tools/damon/schemes.py
>
Jonathan Cameron March 31, 2020, 4:39 p.m. UTC | #2
On Tue, 31 Mar 2020 18:18:19 +0200
SeongJae Park <sjpark@amazon.com> wrote:

> On Tue, 31 Mar 2020 16:51:55 +0100 Jonathan Cameron <Jonathan.Cameron@Huawei.com> wrote:
> 
> > On Mon, 30 Mar 2020 13:50:35 +0200
> > SeongJae Park <sjpark@amazon.com> wrote:
> >   
> > > From: SeongJae Park <sjpark@amazon.de>
> > > 
> > > DAMON[1] can be used as a primitive for data access awared memory management
> > > optimizations.  That said, users who want such optimizations should run DAMON,
> > > read the monitoring results, analyze it, plan a new memory management scheme,
> > > and apply the new scheme by themselves.  Such efforts will be inevitable for
> > > some complicated optimizations.
> > > 
> > > However, in many other cases, the users could simply want the system to apply a
> > > memory management action to a memory region of a specific size having a
> > > specific access frequency for a specific time.  For example, "page out a memory
> > > region larger than 100 MiB keeping only rare accesses more than 2 minutes", or
> > > "Do not use THP for a memory region larger than 2 MiB rarely accessed for more
> > > than 1 seconds".
> > > 
> > > This RFC patchset makes DAMON to handle such data access monitoring-based
> > > operation schemes.  With this change, users can do the data access awared
> > > optimizations by simply specifying their schemes to DAMON.  
> > 
> > 
> > Hi SeongJae,
> > 
> > I'm wondering if I'm misreading the results below or a data handling mixup
> > occured. See inline.  
> 
> Thank you for question, Jonathan!
> 
> > 
> > Thanks,
> > 
> > Jonathan
> >   
> > >   
> [...]
> > > Results
> > > -------
> > > 
> > > Below two tables show the measurement results.  The runtimes are in seconds
> > > while the memory usages are in KiB.  Each configurations except 'orig' shows
> > > its overhead relative to 'orig' in percent within parenthesises.
> > > 
> > > runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
> > > parsec3/blackscholes    107.594  107.956  (0.34)     106.750  (-0.78)    107.672  (0.07)     111.916  (4.02)    
> > > parsec3/bodytrack       79.230   79.368   (0.17)     78.908   (-0.41)    79.705   (0.60)     80.423   (1.50)    
> > > parsec3/canneal         142.831  143.810  (0.69)     123.530  (-13.51)   133.778  (-6.34)    144.998  (1.52)    
> > > parsec3/dedup           11.986   11.959   (-0.23)    11.762   (-1.87)    12.028   (0.35)     13.313   (11.07)   
> > > parsec3/facesim         210.125  209.007  (-0.53)    205.226  (-2.33)    207.766  (-1.12)    209.815  (-0.15)   
> > > parsec3/ferret          191.601  191.177  (-0.22)    190.420  (-0.62)    191.775  (0.09)     192.638  (0.54)    
> > > parsec3/fluidanimate    212.735  212.970  (0.11)     209.151  (-1.68)    211.904  (-0.39)    218.573  (2.74)    
> > > parsec3/freqmine        291.225  290.873  (-0.12)    289.258  (-0.68)    289.884  (-0.46)    298.373  (2.45)    
> > > parsec3/raytrace        118.289  119.586  (1.10)     119.045  (0.64)     119.064  (0.66)     137.919  (16.60)   
> > > parsec3/streamcluster   323.565  328.168  (1.42)     279.565  (-13.60)   287.452  (-11.16)   333.244  (2.99)    
> > > parsec3/swaptions       155.140  155.473  (0.21)     153.816  (-0.85)    156.423  (0.83)     156.237  (0.71)    
> > > parsec3/vips            58.979   59.311   (0.56)     58.733   (-0.42)    59.005   (0.04)     61.062   (3.53)    
> > > parsec3/x264            70.539   68.413   (-3.01)    64.760   (-8.19)    67.180   (-4.76)    68.103   (-3.45)   
> > > splash2x/barnes         80.414   81.751   (1.66)     73.585   (-8.49)    80.232   (-0.23)    115.753  (43.95)   
> > > splash2x/fft            33.902   34.111   (0.62)     24.228   (-28.53)   29.926   (-11.73)   44.438   (31.08)   
> > > splash2x/lu_cb          85.556   86.001   (0.52)     84.538   (-1.19)    86.000   (0.52)     91.447   (6.89)    
> > > splash2x/lu_ncb         93.399   93.652   (0.27)     90.463   (-3.14)    94.008   (0.65)     93.901   (0.54)    
> > > splash2x/ocean_cp       45.253   45.191   (-0.14)    43.049   (-4.87)    44.022   (-2.72)    46.588   (2.95)    
> > > splash2x/ocean_ncp      86.927   87.065   (0.16)     50.747   (-41.62)   86.855   (-0.08)    199.553  (129.57)  
> > > splash2x/radiosity      91.433   91.511   (0.09)     90.626   (-0.88)    91.865   (0.47)     104.524  (14.32)   
> > > splash2x/radix          31.923   32.023   (0.31)     25.194   (-21.08)   32.035   (0.35)     39.231   (22.89)   
> > > splash2x/raytrace       84.367   84.677   (0.37)     82.417   (-2.31)    83.505   (-1.02)    84.857   (0.58)    
> > > splash2x/volrend        87.499   87.495   (-0.00)    86.775   (-0.83)    87.311   (-0.21)    87.511   (0.01)    
> > > splash2x/water_nsquared 236.397  236.759  (0.15)     219.902  (-6.98)    224.228  (-5.15)    238.562  (0.92)    
> > > splash2x/water_spatial  89.646   89.767   (0.14)     89.735   (0.10)     90.347   (0.78)     103.585  (15.55)   
> > > total                   3020.570 3028.080 (0.25)     2852.190 (-5.57)    2953.960 (-2.21)    3276.550 (8.47)    
> > > 
> > > 
> > > memused.avg             orig         rec          (overhead) thp          (overhead) ethp         (overhead) prcl         (overhead)
> > > parsec3/blackscholes    1785916.600  1834201.400  (2.70)     1826249.200  (2.26)     1828079.200  (2.36)     1712210.600  (-4.13)   
> > > parsec3/bodytrack       1415049.400  1434317.600  (1.36)     1423715.000  (0.61)     1430392.600  (1.08)     1435136.000  (1.42)    
> > > parsec3/canneal         1043489.800  1058617.600  (1.45)     1040484.600  (-0.29)    1048664.800  (0.50)     1050280.000  (0.65)    
> > > parsec3/dedup           2414453.200  2458493.200  (1.82)     2411379.400  (-0.13)    2400516.000  (-0.58)    2461120.800  (1.93)    
> > > parsec3/facesim         541597.200   550097.400   (1.57)     544364.600   (0.51)     553240.000   (2.15)     552316.400   (1.98)    
> > > parsec3/ferret          317986.600   332346.000   (4.52)     320218.000   (0.70)     331085.000   (4.12)     330895.200   (4.06)    
> > > parsec3/fluidanimate    576183.400   585442.000   (1.61)     577780.200   (0.28)     587703.400   (2.00)     506501.000   (-12.09)  
> > > parsec3/freqmine        990869.200   997817.000   (0.70)     990350.400   (-0.05)    997669.000   (0.69)     763325.800   (-22.96)  
> > > parsec3/raytrace        1748370.800  1757109.200  (0.50)     1746153.800  (-0.13)    1757830.400  (0.54)     1581455.800  (-9.55)   
> > > parsec3/streamcluster   121521.800   140452.400   (15.58)    129725.400   (6.75)     132266.000   (8.84)     130558.200   (7.44)    
> > > parsec3/swaptions       15592.400    29018.800    (86.11)    14765.800    (-5.30)    27260.200    (74.83)    26631.600    (70.80)   
> > > parsec3/vips            2957567.600  2967993.800  (0.35)     2956623.200  (-0.03)    2973062.600  (0.52)     2951402.000  (-0.21)   
> > > parsec3/x264            3169012.400  3175048.800  (0.19)     3190345.400  (0.67)     3189353.000  (0.64)     3172924.200  (0.12)    
> > > splash2x/barnes         1209066.000  1213125.400  (0.34)     1217261.400  (0.68)     1209661.600  (0.05)     921041.800   (-23.82)  
> > > splash2x/fft            9359313.200  9195213.000  (-1.75)    9377562.400  (0.19)     9050957.600  (-3.29)    9517977.000  (1.70)    
> > > splash2x/lu_cb          514966.200   522939.400   (1.55)     520870.400   (1.15)     522635.000   (1.49)     329933.600   (-35.93)  
> > > splash2x/lu_ncb         514180.400   525974.800   (2.29)     521420.200   (1.41)     521063.600   (1.34)     523557.000   (1.82)    
> > > splash2x/ocean_cp       3346493.400  3288078.000  (-1.75)    3382253.800  (1.07)     3289477.600  (-1.70)    3260810.400  (-2.56)   
> > > splash2x/ocean_ncp      3909966.400  3882968.800  (-0.69)    7037196.000  (79.98)    4046363.400  (3.49)     3471452.400  (-11.22)  
> > > splash2x/radiosity      1471119.400  1470626.800  (-0.03)    1482604.200  (0.78)     1472718.400  (0.11)     546893.600   (-62.82)  
> > > splash2x/radix          1748360.800  1729163.400  (-1.10)    1371463.200  (-21.56)   1701993.600  (-2.65)    1817519.600  (3.96)    
> > > splash2x/raytrace       46670.000    60172.200    (28.93)    51901.600    (11.21)    60782.600    (30.24)    52644.800    (12.80)   
> > > splash2x/volrend        150666.600   167444.200   (11.14)    151335.200   (0.44)     163345.000   (8.41)     162760.000   (8.03)    
> > > splash2x/water_nsquared 45720.200    59422.400    (29.97)    46031.000    (0.68)     61801.400    (35.17)    62627.000    (36.98)   
> > > splash2x/water_spatial  663052.200   672855.800   (1.48)     665787.600   (0.41)     674696.200   (1.76)     471052.600   (-28.96)  
> > > total                   40077300.000 40108900.000 (0.08)     42997900.000 (7.29)     40032700.000 (-0.11)    37813000.000 (-5.65)   
> > > 
> > >   
> [...]
> > > 
> > > Efficient THP
> > > ~~~~~~~~~~~~~
> > > 
> > > THP 'always' enabled policy achieves 5.57% speedup but incurs 7.29% memory
> > > overhead.  It achieves 41.62% speedup in best case, but 79.98% memory overhead
> > > in worst case.  Interestingly, both the best and worst case are with
> > > 'splash2x/ocean_ncp').  
> > 
> > The results above don't seems to support this any more? 
> >   
> > > runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
> > > splash2x/ocean_ncp      86.927   87.065   (0.16)     50.747   (-41.62)   86.855   (-0.08)    199.553  (129.57)   
> 
> Hmm... But, I don't get what point you meaning...  In the data, column of 'thp'
> means the THP 'always' enabled policy.  And, the following column shows the
> overhead of it compared to that of 'orig', in percent.  Thus, the data says THP
> 'always' enabled policy enabled kernel consumes 50.747 seconds to finish
> splash2x/ocean_ncp, while THP disabled original kernel consumes 86.927 seconds.

ah. I got myself confused. 

However, I was expecting to see a significant performance advantage
to ethp for this particular case as we did in the previous version.

In the previous version (you posted in reply to v6 of Damon), for ethp we had a significant gain with:

runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
splash2x/ocean_ncp      81.360   81.434   (0.09)     51.157   (-37.12)   66.711   (-18.00)   91.611   (12.60) 

So, in ethp we got roughly half the performance back (at the cost of some of the memory)

That was a result I have been trying to replicate, hence was at the front of my mind!

Any idea why that changed so much? 

Thanks,

Jonathan


> Thus, the overhead is ``(50.747 - 86.927) / 86.927 = -0.4162``.  In other
> words, 41.62% speedup.
> 
> Also, 5.57% speedup and 7.29% memory overhead is for _total_.  This data shows
> it.
> 
> > > runtime                 orig     rec      (overhead) thp      (overhead) ethp     (overhead) prcl     (overhead)
> > > total                   3020.570 3028.080 (0.25)     2852.190 (-5.57)    2953.960 (-2.21)    3276.550 (8.47)      
> 
> Maybe I made you confused by ambiguously saying this.  Sorry if so.  Or, if I'm
> still misunderstanding your point, please let me know.


> 
> 
> Thanks,
> SeongJae Park
>  
> [...]