Does ftl
have private storage space that is not flash?
If not, how does ftl
store those meta data while avoiding wear leveling
.
Actually I don’t know if there is a super block in ftl
, but if you want to locate the mapping data and unusable block whose physical address changes frequently, a certain physical address may be needed. The content on this physical address must change frequently, how To avoid wear leveling of this physical address?
There are many possible solutions to this problem and it's very intertwined with the data representation that the drive uses to store its data, so I'm sure it differs a lot based on the drive / manufacturer. I'll just outline a general approach that could work.
Let's say you design an FTL that maintains several fixed-size, append-only "logs", and for simplicity we always have one "active" log that all writes are appended to. If the user is issuing random writes, the order of LBAs in the active log will be random too. When the active log fills all the space allocated to it, it gets "frozen" and we switch the active log to some empty log elsewhere in the flash. As the data in the frozen log becomes stale, we will eventually need to garbage collect it by copying any still-referenced blocks to a different log before erasing the original so that it can be reused for new writes.
Now, for each write to a log, nothing in our interface so far requires that the blocks be exactly 4KiB (or whatever), so you could append a small header to the data that tells you what its LBA is, and perhaps some other metadata -- write sequence number so you can tell if it's the most recent copy of a block, and maybe a checksum for read integrity checking. When a write finishes, you update an in-RAM copy of the map with the new location for the LBAs that were updated (RAM inside the SSD, not RAM for the main CPU of the computer obviously).
If the FTL crashes or loses power, you can reconstruct the map by reading all headers from all the logs. The downside is that scanning the logs will scale
O(number of logs * number of blocks per log)
, so you optimize that somehow:O(number of logs * (log_2(number of blocks per log) + number of blocks that need to be scanned))
So far, this lowers how often you need to write the map by a lot, but it's still probably too often to overwrite it to a fixed location for a drive with a very long lifetime. To resolve that, we have to cycle where we write the map:
O(X * log_2(number of maps per log) + runtime to scan the other logs if unclean shutdown)
.Another aspect of this is that full map flushes could be expensive, which would add tail latency if it ever interferes with the performance of user IOs -- would it be better to allow incremental updates? That's when you start looking at using something like a log-structured merge (LSM) tree to store your map, so that each incremental write is pretty small and you can amortize the full map write cost.
Obviously there are a bunch of tiny details that this explanation leaves out, but hopefully that's enough to get you started. :-)