The only way to determine that would be to have them run both a M dash and a marathon, and assess their performance half-way through the marathon. With a data-reduction SSD, the lower the entropy of the data coming from the host computer, the less the SSD has to write to the flash memory, leaving more space for over provisioning.
Write amplification in this phase will increase to the highest levels the drive will experience. So this a rare instance when an amplifier — namely, Write Amplification — makes something smaller. And of course the worst case — of writing 11 times more than STCS — is terrible.
CrystalDiskMark could be a good choice because it can test with both low and high entropy data, with the latter being the default configuration.
The reason is that most of the data is stored in the biggest level, and since this level is a run — with different sstables having no overlap — we cannot have any duplicates inside this run.
Doing the math When you find candidates that might be a match you might have multiple attributessecure erase the drive again, this time writing randomly with 4K transfers. With LCS, this problem is gone, as we can see in the graph below: One free tool write amplification test is commonly referenced in the industry is called HDDerase.
For write amplification test to know what each attribute represents, the program reading the attribute has to be pre-programmed by the manufacturer. Each time data are relocated without being changed by the host system, this increases the write amplification and thus reduces the life of the flash memory.
Accommodating these differences increases the time and effort it takes to get meaningful results, and therein lies the reason for the lies common in SSD benchmark testing. We call this undesirable effect write amplification WA. If disk bandwidth needed by writes exceeds what we can do, LCS compaction can no longer keep up.
If the user saves data consuming only half of the total user capacity of the drive, the other half of the user capacity will look like additional over-provisioning as long as the TRIM command is supported in the system.
The TRIM command is used by the operating system to specify which pages of data stored on an SSD no longer contain valid data, and can therefore be ignored deleted during garbage collection.
With an SSD without integrated encryption, this command will put the drive back to its original out-of-box state.
For this reason, Scylla and Cassandra have an emergency mode, where if we have too many sstables piling up in L0, STCS is done inside L0 to at least replace the many small files thereby fewer, larger, files. The process requires the SSD controller to separate the LBAs with data which is constantly changing and requiring rewriting dynamic data from the LBAs with data which rarely changes and does not require any rewrites static data.
And because these results were achieved by following the best practices outlined here, it is possible to interpolate the findings for a particular mix of random and sequential data. The level of entropy of the data also has an effect whenever testing any SSD that employs a data reduction technology.
Once the blocks are all written once, garbage collection will begin and the performance will be gated by the speed and efficiency of that process.
But because SSD behavior is very different for sequential vs. In the previous postwe introduced the Size-Tiered compaction strategy STCS and discussed its most significant drawback — its disk-space waste, a.
The portion of the user capacity which is free from user data either already TRIMed or never written in the first place will look the same as over-provisioning space until the user saves new data to the SSD. You want to write about 10 or more times the physical capacity of the SSD.
The reason is as the data is written, the entire block is filled sequentially with data related to the same file. The benefit of using a run of fragments small sstables instead of one huge sstable is that with a run, we can compact only parts of the huge sstable instead of all of it.
The result of this compaction is a new run large sstable split by our chosen size limit, by default MB which we put in L1, replacing the entire content of L1. Reading the Results A brand new or freshly-erased SSD exhibits astonishing performance, because there is no need to move any old data before writing new data.
Instead, SSDs use a process called garbage collection GC to reclaim the space taken by previously stored data. Good SSD benchmark testing takes time—several hours or more to test each disk—so it is tempting to take short-cuts.
This is bad because the flash memory in the SSD supports only a limited number of writes before it can no longer be read. If the SSD has a high write amplification, the controller will be required to write that many more times to the flash memory. To calculate write amplification, use this equation: The best case for LCS is that the last level is filled.
With size-tiered compaction, we saw huge space amplification — as much as 9. With this method, you should be able to measure the write amplification of any SSD as long as it has erase cycles and host data-written attributes or something that closely represents them.
In this article we examined all the elements that affect WA, including the implications and advantages of a data reduction technology like LSI SandForce's DuraWrite technology. In this post, we will look at Leveled Compaction Strategy LCSthe first alternative compaction strategy designed to solve the space amplification problem of STCS, and show that it does solve that problem, but unfortunately introduces a new problem — write amplification.
DuraWrite technology increases the free space mentioned above, but in a way that is unique from other SSD controllers. Data reduction technology can master data entropy The performance of all SSDs is influenced by the same factors — such as the amount of over provisioning and levels of random vs.Write amplification was initially proposed for the Intel and Silicon Systems in Coulson , an Intel senior Fellow, introduced a way of calculating write amplification.
Hu  suggested a probability analytical model to study the relationship between over-provisioning and write amplification. Calculating the Write Amplification Factor WAF is an attribute that tracks the multiplicative effect of additional writes that result from WA.
WAF is the ratio of total. The write amplification factor is the amount of data the SSD controller has to write in relation to the amount of data that the host controller wants to write.
2 Factors Affecting Write Amplification (WA) Factors that can contribute to write amplification are: 1. There is no WA until the SSD is written to full capacity for the 1st time 2.
Sequential writes (have lower WA) vs. Random writes (higher WA) 3. Transaction size (the larger the transaction, the lower the WA) 4. Write Endurance 05/ Since we know that 1 Terabyte was written over the 72 hour test we can calculate that this drive will last days or you can see, write amplification is critical to the life expectancy of the drive.
These values are. Endurance Testing: Write Amplification And Estimated Lifespan SandForce's Technology: Very Low Write Amplification.
According to SandForce, SSD manufacturers can tweak firmware in a number of.Download