Positively SQL

In previous posts I talked about the wear and RAISE algorithms implemented by SSD controllers. One of the inevitable issues solid state memory is how to gracefully deal with bad blocks.

Bad blocks are flash memory blocks that contain one or more invalid bits whose reliability is not guaranteed because of faulty dies, over-charge leaks or wear-out. Bad blocks may exist even on a new disk.

Bad Block Management or Intelligent Block Management is an algorithm that monitors and maintains bad blocks within the NAND device. The controller maintains tables of known bad blocks and can replace the new bad blocks with spare blocks that are reserved for use. typically 4-10% of the usable capacity is reserved for Bad Block Management This practice further enhances the overall SSD lifespan and ensures that a few bad blocks will not affect the integrity of the drive and the SSD device still operate.

Bad blocks are mapped as “do not use”and substituted with known good blocks from the percentage set aside for spare blocks. The percentage of bad blocks which can be accomodated is a product marketing decision and that is the reason why an 128GB SSD device will only present 120GB as available to use. The spare blocks come from over provisioning inside the SSD and using the capacity which is invisible to the user.

If the bad blocks exceed the remaining spare blocks for any reason- the SSD fails because the controller cannot safely substitute a block that has to be written on a new bad block and can result in data loss.

Retired block count

The measure for Bad Block Management is “Retired Block Count” but expect that count to go up as “SSD Life Left” nears 5-10%

Wear leveling is a technology used in Solid State Drive  controllers to prolong the service life of flash memory. As mentioned in the 2nd post of this blog series  What’s the difference between SLC and MLC? flash memories have limited endurance,measured by the number of P/E cycles that the memory can perform before becoming degraded. Wear leveling ensures that all cells are getting the same number of P/E cycles (even wear) so that you do not have  just a few cells on the drive receive the majority of the writes and wear out early. This might cause the drive to fail when most of the memory on it is still usable way ahead of the prescribed service life.

Memory wear-out concerns are unique to flash-based memory. Hard disks store data by magnetizing a thin film of ferromagnetic material on a disk. DRAM is volatile memory  (the memory stores data only while it is powered on). Flash memory stores data inside the NAND cell  via a process called tunneling while the floating gate is being flooded with high voltage. This leaves a charge in the NAND cell and that charge can be read over and over. Because  of this invasive writing method and coresponding erasing method, the flash cells degrade over time.

Wear leveling algorithm basically stores the P/E count of each cell and writes the next block to the  “least used available cell” so that cells that were intensively used are put to the end of the queue until all cells have an even wear.

One caveat is that new disks will have a much better performance than the once that were used intensively because all cells are good candidates for writing. Once the disk has been used, there is a performance degradation due to the need to erase  the cell selected by wear leveling. So a good advice would be not to test a new drive but first perform writes on 2-3 times the capacity of the drive before starting tests(e.g. 240GB SSD drive should have 500-750GB lifetime writes) in order to simulate the a real production scenario instead of just  benchmarking a brand new disk. One other thing that affects this performance is Static Data Rotation which is discussed in the first post of the series. Lifetime writes can be queried using Cristal DiskInfo and other free tools.

Disk parameters to check