linux-stable/fs/erofs/Kconfig

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# SPDX-License-Identifier: GPL-2.0-only
config EROFS_FS
tristate "EROFS filesystem support"
depends on BLOCK
select FS_IOMAP
select LIBCRC32C
help
EROFS (Enhanced Read-Only File System) is a lightweight read-only
file system with modern designs (e.g. no buffer heads, inline
xattrs/data, chunk-based deduplication, multiple devices, etc.) for
scenarios which need high-performance read-only solutions, e.g.
smartphones with Android OS, LiveCDs and high-density hosts with
numerous containers;
It also provides fixed-sized output compression support in order to
improve storage density as well as keep relatively higher compression
ratios and implements in-place decompression to reuse the file page
for compressed data temporarily with proper strategies, which is
quite useful to ensure guaranteed end-to-end runtime decompression
performance under extremely memory pressure without extra cost.
See the documentation at <file:Documentation/filesystems/erofs.rst>
and the web pages at <https://erofs.docs.kernel.org> for more details.
If unsure, say N.
config EROFS_FS_DEBUG
bool "EROFS debugging feature"
depends on EROFS_FS
help
Print debugging messages and enable more BUG_ONs which check
filesystem consistency and find potential issues aggressively,
which can be used for Android eng build, for example.
For daily use, say N.
config EROFS_FS_XATTR
bool "EROFS extended attributes"
depends on EROFS_FS
select XXHASH
default y
help
Extended attributes are name:value pairs associated with inodes by
the kernel or by users (see the attr(5) manual page, or visit
<http://acl.bestbits.at/> for details).
If unsure, say N.
config EROFS_FS_POSIX_ACL
bool "EROFS Access Control Lists"
depends on EROFS_FS_XATTR
select FS_POSIX_ACL
default y
help
Posix Access Control Lists (ACLs) support permissions for users and
groups beyond the owner/group/world scheme.
To learn more about Access Control Lists, visit the POSIX ACLs for
Linux website <http://acl.bestbits.at/>.
If you don't know what Access Control Lists are, say N.
config EROFS_FS_SECURITY
bool "EROFS Security Labels"
depends on EROFS_FS_XATTR
default y
help
Security labels provide an access control facility to support Linux
Security Models (LSMs) accepted by AppArmor, SELinux, Smack and TOMOYO
Linux. This option enables an extended attribute handler for file
security labels in the erofs filesystem, so that it requires enabling
the extended attribute support in advance.
If you are not using a security module, say N.
config EROFS_FS_ZIP
bool "EROFS Data Compression Support"
depends on EROFS_FS
select LZ4_DECOMPRESS
default y
help
Enable fixed-sized output compression for EROFS.
If you don't want to enable compression feature, say N.
config EROFS_FS_ZIP_LZMA
bool "EROFS LZMA compressed data support"
depends on EROFS_FS_ZIP
select XZ_DEC
select XZ_DEC_MICROLZMA
help
Saying Y here includes support for reading EROFS file systems
containing LZMA compressed data, specifically called microLZMA. It
gives better compression ratios than the default LZ4 format, at the
expense of more CPU overhead.
If unsure, say N.
erofs: DEFLATE compression support Add DEFLATE compression as the 3rd supported algorithm. DEFLATE is a popular generic-purpose compression algorithm for quite long time (many advanced formats like gzip, zlib, zip, png are all based on that) as Apple documentation written "If you require interoperability with non-Apple devices, use COMPRESSION_ZLIB. [1]". Due to its popularity, there are several hardware on-market DEFLATE accelerators, such as (s390) DFLTCC, (Intel) IAA/QAT, (HiSilicon) ZIP accelerator, etc. In addition, there are also several high-performence IP cores and even open-source FPGA approches available for DEFLATE. Therefore, it's useful to support DEFLATE compression in order to find a way to utilize these accelerators for asynchronous I/Os and get benefits from these later. Besides, it's a good choice to trade off between compression ratios and performance compared to LZ4 and LZMA. The DEFLATE core format is simple as well as easy to understand, therefore the code size of its decompressor is small even for the bootloader use cases. The runtime memory consumption is quite limited too (e.g. 32K + ~7K for each zlib stream). As usual, EROFS ourperforms similar approaches too. Alternatively, DEFLATE could still be used for some specific files since EROFS supports multiple compression algorithms in one image. [1] https://developer.apple.com/documentation/compression/compression_algorithm Reviewed-by: Chao Yu <chao@kernel.org> Signed-off-by: Gao Xiang <hsiangkao@linux.alibaba.com> Link: https://lore.kernel.org/r/20230810154859.118330-1-hsiangkao@linux.alibaba.com
2023-08-10 15:48:59 +00:00
config EROFS_FS_ZIP_DEFLATE
bool "EROFS DEFLATE compressed data support"
depends on EROFS_FS_ZIP
select ZLIB_INFLATE
help
Saying Y here includes support for reading EROFS file systems
containing DEFLATE compressed data. It gives better compression
ratios than the default LZ4 format, while it costs more CPU
overhead.
DEFLATE support is an experimental feature for now and so most
file systems will be readable without selecting this option.
If unsure, say N.
config EROFS_FS_ONDEMAND
bool "EROFS fscache-based on-demand read support"
depends on EROFS_FS
select NETFS_SUPPORT
select FSCACHE
select CACHEFILES
select CACHEFILES_ONDEMAND
help
This permits EROFS to use fscache-backed data blobs with on-demand
read support.
If unsure, say N.
erofs: add per-cpu threads for decompression as an option Using per-cpu thread pool we can reduce the scheduling latency compared to workqueue implementation. With this patch scheduling latency and variation is reduced as per-cpu threads are high priority kthread_workers. The results were evaluated on arm64 Android devices running 5.10 kernel. The table below shows resulting improvements of total scheduling latency for the same app launch benchmark runs with 50 iterations. Scheduling latency is the latency between when the task (workqueue kworker vs kthread_worker) became eligible to run to when it actually started running. +-------------------------+-----------+----------------+---------+ | | workqueue | kthread_worker | diff | +-------------------------+-----------+----------------+---------+ | Average (us) | 15253 | 2914 | -80.89% | | Median (us) | 14001 | 2912 | -79.20% | | Minimum (us) | 3117 | 1027 | -67.05% | | Maximum (us) | 30170 | 3805 | -87.39% | | Standard deviation (us) | 7166 | 359 | | +-------------------------+-----------+----------------+---------+ Background: Boot times and cold app launch benchmarks are very important to the Android ecosystem as they directly translate to responsiveness from user point of view. While EROFS provides a lot of important features like space savings, we saw some performance penalty in cold app launch benchmarks in few scenarios. Analysis showed that the significant variance was coming from the scheduling cost while decompression cost was more or less the same. Having per-cpu thread pool we can see from the above table that this variation is reduced by ~80% on average. This problem was discussed at LPC 2022. Link to LPC 2022 slides and talk at [1] [1] https://lpc.events/event/16/contributions/1338/ [ Gao Xiang: At least, we have to add this until WQ_UNBOUND workqueue issue [2] on many arm64 devices is resolved. ] [2] https://lore.kernel.org/r/CAJkfWY490-m6wNubkxiTPsW59sfsQs37Wey279LmiRxKt7aQYg@mail.gmail.com Signed-off-by: Sandeep Dhavale <dhavale@google.com> Signed-off-by: Gao Xiang <hsiangkao@linux.alibaba.com> Link: https://lore.kernel.org/r/20230208093322.75816-1-hsiangkao@linux.alibaba.com
2023-02-08 09:33:22 +00:00
config EROFS_FS_PCPU_KTHREAD
bool "EROFS per-cpu decompression kthread workers"
depends on EROFS_FS_ZIP
help
Saying Y here enables per-CPU kthread workers pool to carry out
async decompression for low latencies on some architectures.
If unsure, say N.
config EROFS_FS_PCPU_KTHREAD_HIPRI
bool "EROFS high priority per-CPU kthread workers"
depends on EROFS_FS_ZIP && EROFS_FS_PCPU_KTHREAD
default y
erofs: add per-cpu threads for decompression as an option Using per-cpu thread pool we can reduce the scheduling latency compared to workqueue implementation. With this patch scheduling latency and variation is reduced as per-cpu threads are high priority kthread_workers. The results were evaluated on arm64 Android devices running 5.10 kernel. The table below shows resulting improvements of total scheduling latency for the same app launch benchmark runs with 50 iterations. Scheduling latency is the latency between when the task (workqueue kworker vs kthread_worker) became eligible to run to when it actually started running. +-------------------------+-----------+----------------+---------+ | | workqueue | kthread_worker | diff | +-------------------------+-----------+----------------+---------+ | Average (us) | 15253 | 2914 | -80.89% | | Median (us) | 14001 | 2912 | -79.20% | | Minimum (us) | 3117 | 1027 | -67.05% | | Maximum (us) | 30170 | 3805 | -87.39% | | Standard deviation (us) | 7166 | 359 | | +-------------------------+-----------+----------------+---------+ Background: Boot times and cold app launch benchmarks are very important to the Android ecosystem as they directly translate to responsiveness from user point of view. While EROFS provides a lot of important features like space savings, we saw some performance penalty in cold app launch benchmarks in few scenarios. Analysis showed that the significant variance was coming from the scheduling cost while decompression cost was more or less the same. Having per-cpu thread pool we can see from the above table that this variation is reduced by ~80% on average. This problem was discussed at LPC 2022. Link to LPC 2022 slides and talk at [1] [1] https://lpc.events/event/16/contributions/1338/ [ Gao Xiang: At least, we have to add this until WQ_UNBOUND workqueue issue [2] on many arm64 devices is resolved. ] [2] https://lore.kernel.org/r/CAJkfWY490-m6wNubkxiTPsW59sfsQs37Wey279LmiRxKt7aQYg@mail.gmail.com Signed-off-by: Sandeep Dhavale <dhavale@google.com> Signed-off-by: Gao Xiang <hsiangkao@linux.alibaba.com> Link: https://lore.kernel.org/r/20230208093322.75816-1-hsiangkao@linux.alibaba.com
2023-02-08 09:33:22 +00:00
help
This permits EROFS to configure per-CPU kthread workers to run
at higher priority.
If unsure, say N.