Presentation
CiS: In-Storage Compression for Improving Read Performance of NAND Flash-based SSDs
DescriptionModern data storage systems heavily rely on SSDs
due to their high speed and efficiency. With the rise of data-
intensive applications, particularly in deep learning, the demand
for increased storage capacity is more pressing than ever. To
address this challenge, we propose Compression in SSDs (CiS),
an approach to enhance storage performance and reliability by
applying data compression techniques within SSDs. By compress-
ing user data and storing it in NAND flash, the number of bitlines
selected within the NAND flash during a read operation can
be effectively reduced. Reducing the number of selected bitlines
during read operations helps mitigate read-retry occurrences that
may arise due to read disturbance effects. This paper examines
various compression algorithms for storing user data in NAND
flash-based SSDs and evaluates their effects on compression ratio
and storage reliability. Our findings demonstrate that strategic
grouping of similar file types in data centers, coupled with
the application of appropriate compression algorithms, can lead
to significant improvements in storage read performance by
reducing read-retry counts. The results show that CiS reduced the
read-retry count by an average of 32%, 62%, and 88% compared
to the baseline when the compression ratios were 4/3, 2, and 4,
respectively.
due to their high speed and efficiency. With the rise of data-
intensive applications, particularly in deep learning, the demand
for increased storage capacity is more pressing than ever. To
address this challenge, we propose Compression in SSDs (CiS),
an approach to enhance storage performance and reliability by
applying data compression techniques within SSDs. By compress-
ing user data and storing it in NAND flash, the number of bitlines
selected within the NAND flash during a read operation can
be effectively reduced. Reducing the number of selected bitlines
during read operations helps mitigate read-retry occurrences that
may arise due to read disturbance effects. This paper examines
various compression algorithms for storing user data in NAND
flash-based SSDs and evaluates their effects on compression ratio
and storage reliability. Our findings demonstrate that strategic
grouping of similar file types in data centers, coupled with
the application of appropriate compression algorithms, can lead
to significant improvements in storage read performance by
reducing read-retry counts. The results show that CiS reduced the
read-retry count by an average of 32%, 62%, and 88% compared
to the baseline when the compression ratios were 4/3, 2, and 4,
respectively.
Event Type
Networking
Work-in-Progress Poster
TimeSunday, June 226:00pm - 7:00pm PDT
LocationLevel 3 Lobby