2015-03-23 09:32:16 +01:00
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Use multiple thread (de)compression in live migration
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=====================================================
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Copyright (C) 2015 Intel Corporation
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Author: Liang Li <liang.z.li@intel.com>
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This work is licensed under the terms of the GNU GPLv2 or later. See
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the COPYING file in the top-level directory.
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Contents:
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=========
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* Introduction
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* When to use
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* Performance
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* Usage
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* TODO
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Introduction
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============
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Instead of sending the guest memory directly, this solution will
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compress the RAM page before sending; after receiving, the data will
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be decompressed. Using compression in live migration can help
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to reduce the data transferred about 60%, this is very useful when the
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bandwidth is limited, and the total migration time can also be reduced
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about 70% in a typical case. In addition to this, the VM downtime can be
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reduced about 50%. The benefit depends on data's compressibility in VM.
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The process of compression will consume additional CPU cycles, and the
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extra CPU cycles will increase the migration time. On the other hand,
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the amount of data transferred will decrease; this factor can reduce
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the total migration time. If the process of the compression is quick
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enough, then the total migration time can be reduced, and multiple
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thread compression can be used to accelerate the compression process.
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The decompression speed of Zlib is at least 4 times as quick as
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compression, if the source and destination CPU have equal speed,
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keeping the compression thread count 4 times the decompression
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thread count can avoid resource waste.
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Compression level can be used to control the compression speed and the
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compression ratio. High compression ratio will take more time, level 0
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stands for no compression, level 1 stands for the best compression
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speed, and level 9 stands for the best compression ratio. Users can
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select a level number between 0 and 9.
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When to use the multiple thread compression in live migration
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=============================================================
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Compression of data will consume extra CPU cycles; so in a system with
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high overhead of CPU, avoid using this feature. When the network
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bandwidth is very limited and the CPU resource is adequate, use of
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multiple thread compression will be very helpful. If both the CPU and
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the network bandwidth are adequate, use of multiple thread compression
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can still help to reduce the migration time.
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Performance
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===========
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Test environment:
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CPU: Intel(R) Xeon(R) CPU E5-2680 0 @ 2.70GHz
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Socket Count: 2
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RAM: 128G
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NIC: Intel I350 (10/100/1000Mbps)
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Host OS: CentOS 7 64-bit
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Guest OS: RHEL 6.5 64-bit
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2018-06-13 07:05:19 +02:00
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Parameter: qemu-system-x86_64 -accel kvm -smp 4 -m 4096
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2015-03-23 09:32:16 +01:00
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/share/ia32e_rhel6u5.qcow -monitor stdio
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There is no additional application is running on the guest when doing
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the test.
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Speed limit: 1000Gb/s
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---------------------------------------------------------------
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| original | compress thread: 8
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| way | decompress thread: 2
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| | compression level: 1
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---------------------------------------------------------------
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total time(msec): | 3333 | 1833
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---------------------------------------------------------------
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downtime(msec): | 100 | 27
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---------------------------------------------------------------
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transferred ram(kB):| 363536 | 107819
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---------------------------------------------------------------
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throughput(mbps): | 893.73 | 482.22
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---------------------------------------------------------------
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total ram(kB): | 4211524 | 4211524
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---------------------------------------------------------------
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There is an application running on the guest which write random numbers
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to RAM block areas periodically.
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Speed limit: 1000Gb/s
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---------------------------------------------------------------
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| original | compress thread: 8
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| way | decompress thread: 2
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| | compression level: 1
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---------------------------------------------------------------
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total time(msec): | 37369 | 15989
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---------------------------------------------------------------
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downtime(msec): | 337 | 173
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---------------------------------------------------------------
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transferred ram(kB):| 4274143 | 1699824
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---------------------------------------------------------------
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throughput(mbps): | 936.99 | 870.95
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---------------------------------------------------------------
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total ram(kB): | 4211524 | 4211524
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---------------------------------------------------------------
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Usage
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=====
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1. Verify both the source and destination QEMU are able
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to support the multiple thread compression migration:
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2016-05-23 11:43:57 +02:00
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{qemu} info migrate_capabilities
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2015-03-23 09:32:16 +01:00
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{qemu} ... compress: off ...
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2. Activate compression on the source:
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{qemu} migrate_set_capability compress on
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3. Set the compression thread count on source:
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2023-08-25 17:59:22 +02:00
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{qemu} migrate_set_parameter compress-threads 12
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2015-03-23 09:32:16 +01:00
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4. Set the compression level on the source:
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2023-08-25 17:59:22 +02:00
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{qemu} migrate_set_parameter compress-level 1
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2015-03-23 09:32:16 +01:00
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5. Set the decompression thread count on destination:
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2023-08-25 17:59:22 +02:00
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{qemu} migrate_set_parameter decompress-threads 3
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2015-03-23 09:32:16 +01:00
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6. Start outgoing migration:
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{qemu} migrate -d tcp:destination.host:4444
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{qemu} info migrate
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Capabilities: ... compress: on
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...
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The following are the default settings:
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compress: off
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2023-08-25 17:59:22 +02:00
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compress-threads: 8
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decompress-threads: 2
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compress-level: 1 (which means best speed)
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2015-03-23 09:32:16 +01:00
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So, only the first two steps are required to use the multiple
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thread compression in migration. You can do more if the default
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settings are not appropriate.
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TODO
|
|
|
|
====
|
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|
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Some faster (de)compression method such as LZ4 and Quicklz can help
|
|
|
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to reduce the CPU consumption when doing (de)compression. If using
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these faster (de)compression method, less (de)compression threads
|
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are needed when doing the migration.
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