Leverage compression hardware accelerator
This spec proposes to leverage hardware compression accelerator to accelerate: 1) Image compression when uploading volume to glance as image. 2) Image decompression when creating volume from image Change-Id: Ia9961f24c4ce78eec61601bd8308868a31a673d6 Signed-off-by: Liang Fang <liang.a.fang@intel.com>
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Liang Fang
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specs/train/leverage-compression-accelerator.rst
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specs/train/leverage-compression-accelerator.rst
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This work is licensed under a Creative Commons Attribution 3.0 Unported
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License.
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http://creativecommons.org/licenses/by/3.0/legalcode
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================================
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Leverage compression accelerator
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================================
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https://blueprints.launchpad.net/cinder/+spec/leverage-compression-accelerator
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This blueprint proposes to leverage hardware compression accelerator to
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accelerate the image compression when uploading volume to glance as image.
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Problem description
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===================
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When trying to upload volume to glance as image, currently all the format
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transformation is done by software and the performance is not good.
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For example, when uploading a volume of size 30GB with 12GB data resides,
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select qcow2 as the target image format, currently the tool used to do the
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transformation is qemu-img. This has below problems:
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#. Low compression rate
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After transforming, the output size is 12GB.
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#. High CPU consuming
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During the transforming, CPU usage is about 100%-170% (~ two cores).
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#. Long duration
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The time to transform the volume is about 23 seconds.
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As a contrast, if using hardware accelerator to do the format transformation,
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choose 'gzip' as the target format, the performance is much better. Take Intel
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QAT as the accelerator for example, performance data would be:
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#. Compression rate
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After transforming, the output size is 2.3GB.
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#. CPU consuming
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During the transforming, CPU usage is about 97% (one core).
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#. Duration
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The time to transform the volume is about 9 seconds.
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So the compressed size is only a quarter of its original size, but takes less
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than half the time.
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Use Cases
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=========
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* User wants to upload volume to glance as a compressed image
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Proposed change
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===============
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- Add a new container format 'compressed'
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Cinder don't have an enum to control container format list, rather than disk
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format. But cinder will have specific steps for the 'compressed' container
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format. Refer to below changes.
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The disk format remains unchanged by this spec, it can be any type in enum in
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cinder.api.schemas.volume_actions.volume_upload_image.
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- Add an option to enable/disable the image compression support
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If there's no hardware accelerator exists, then it will fallback to software
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solution to do the compression. But this will consume CPU resource. So this
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spec will add an option to control if the compression feature be enabled or
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not.
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- Add compression tool of famous hardware accelerators into file volume.filters
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The compression tool such as 'qzip' will be added in volume.filters so that
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it can be run by root wrapper
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- Show 'compressed' in the container format list when selecting a volume to
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upload
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This need to be done in cinder client and horizon.
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- Check if there are some hardware accelerators exist in the system
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Go through the accelerator tool list to find if any hardware accelerator
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exist. If none exist, failover to software solution if compressed format
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is selected.
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This will be done in ./cinder/image/accelerator.py, and at last, will call
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the driver of accelerator to check the existence.
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Refer to:
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https://review.opendev.org/#/c/668825/1/cinder/image/accelerator.py
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Function: is_engine_ready
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https://review.opendev.org/#/c/668825/1/cinder/image/accelerators/qat.py
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Function: is_accel_exist
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- Do image compression after convert_image but before uploading to glance
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Call the existing accelerator's tool to do the compression. e.g. if Intel QAT
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device is identified, then call qzip here to do the compression. If no
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accelerator identified, then fallback to software solution, using the tool
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gzip to do the decomression.
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- Do image decompression after downloading from glance but before convert_image
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When creating volume from image, call hardware accelerator to do the
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decompression. If hw accelerator doesn't exist, then fallback to software
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solution, using the tool gzip to do the decomression
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Alternatives
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------------
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Another way is to use the improved processor with software solution only, such
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as gzip. But the cost would be high vs dedicated hardware accelerator, and have
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no performance benefit.
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REST API impact
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---------------
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Add the image type of "compressed" when uploading volume to image
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Data model impact
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-----------------
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None
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Security impact
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---------------
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None
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Notifications impact
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--------------------
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None
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Other end user impact
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---------------------
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None
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Performance Impact
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------------------
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* Less CPU comsuming if hardware accelerator available
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* Less conversion time if hardware accelerator available
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* Smaller image size
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Other deployer impact
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---------------------
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* Need to install the driver and utility tool of the accelerator
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* Can configurate the option to enable/disable compression capability
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Developer impact
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----------------
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* Developers that want to add support for other accelerators need to add
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their tool to root wrap
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Implementation
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==============
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Assignee(s)
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-----------
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Primary assignee:
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Liang Fang <liang.a.fang@intel.com>
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Work Items
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----------
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* During image conversion, switch to hardware accelerator if possible
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* Implement a common framework for hw leverage in image conversion
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* Implement a typical hw accelerator in image conversion
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* Unit test be added
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Dependencies
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============
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None
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Testing
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=======
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* Unit-tests, tempest and other related tests will be implemented.
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* Test case in particular: when creating a volume from an image with
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container_format == 'compressed', but the image contains some format other than
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what Cinder supports. The expected behavior is to fail gracefully.
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Documentation Impact
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====================
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* Documentation will be needed. User documentation on how to use accelerator
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and developer documentation on how to add an additional accelerator
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References
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==========
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_`[1]` https://review.opendev.org/#/c/668825/
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_`[2]` https://review.opendev.org/#/c/668943/
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