Optimize IO performance of file systems for architecture scenarios such as ARM/X86
###Project Description:
1. Relevant background
Currently, EROFS has been widely used in terminal/container scenarios, but it still faces serious performance bottlenecks in some scenarios (limited memory/low compression rate)
2. Existing job
Currently, EROFS has made significant optimizations in decompression, including in situ decompression, multi-threaded decompression, VMAP mapping, KMAP, etc., all of which have greatly improved decompression performance
3. Shortcomings
In low compression scenarios, there is still a significant gap in IO performance compared to ext4/f2fs, and further improvement is needed to maximize performance in critical scenarios such as containers
4. Points for improvement
Improve the decompression performance of erofs and enhance its concurrency and decompression aggregation capabilities; Further explore optimization points to improve decompression performance
5. The ultimate goal of the project
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
###Comprehensive difficulty of the project:
Advanced
###Technical field label:
Operating system storage EROFS file system kernel
###Programming language tags:
C language
###Project output requirements:
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
###Project technical requirements:
1. Have a certain foundation in kernel development and performance bottleneck analysis
2. Have a certain understanding of the storage field
Optimize IO performance of file systems for architecture scenarios such as ARM/X86
###Project Description:
1. Relevant background
Currently, EROFS has been widely used in terminal/container scenarios, but it still faces serious performance bottlenecks in some scenarios (limited memory/low compression rate)
2. Existing job
Currently, EROFS has made significant optimizations in decompression, including in situ decompression, multi-threaded decompression, VMAP mapping, KMAP, etc., all of which have greatly improved decompression performance
3. Shortcomings
In low compression scenarios, there is still a significant gap in IO performance compared to ext4/f2fs, and further improvement is needed to maximize performance in critical scenarios such as containers
4. Points for improvement
Improve the decompression performance of erofs and enhance its concurrency and decompression aggregation capabilities; Further explore optimization points to improve decompression performance
5. The ultimate goal of the project
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
###Comprehensive difficulty of the project:
Advanced
###Technical field label:
Operating system storage EROFS file system kernel
###Programming language tags:
C language
###Project output requirements:
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
###Project technical requirements:
1. Have a certain foundation in kernel development and performance bottleneck analysis
2. Have a certain understanding of the storage field
Optimize IO performance of file systems for architecture scenarios such as ARM/X86
### Project Description:
1. Relevant background
Currently, EROFS has been widely used in terminal/container scenarios, but it still faces serious performance bottlenecks in some scenarios (limited memory/low compression rate)
2. Existing job
Currently, EROFS has made significant optimizations in decompression, including in situ decompression, multi-threaded decompression, VMAP mapping, KMAP, etc., all of which have greatly improved decompression performance
3. Shortcomings
In low compression scenarios, there is still a significant gap in IO performance compared to ext4/f2fs, and further improvement is needed to maximize performance in critical scenarios such as containers
4. Points for improvement
Improve the decompression performance of erofs and enhance its concurrency and decompression aggregation capabilities; Further explore optimization points to improve decompression performance
5. The ultimate goal of the project
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
### Comprehensive difficulty of the project:
Advanced
### Technical field label:
Operating system storage EROFS file system kernel
### Programming language tags:
C language
### Project output requirements:
In scenarios with a compression rate greater than 70%, improve sequential read performance by about 5%
Optimizing code and contributing to the openEuler community
### Project technical requirements:
1. Have a certain foundation in kernel development and performance bottleneck analysis
2. Have a certain understanding of the storage field