Performance in Intel IOMeter Sequential Read & Write Patterns

The array receives a stream of read/write requests with a request queue depth of 4. Every minute the size of the data block changes, so we can see the dependence of the linear read/write speed on the size of the data block. The results are listed in the following table:

For better reading, we divide the arrays into two groups in the diagrams. The graphs represent the dependence of the sequential read speed on the data chunk size:

The arrays reach their maximum speeds at different sizes of the data block when the controller can split a big request into several small ones for the HDDs of the array to process them in parallel. There is a clear dependence of the speed on the number of the disks only with the two- and three-disk RAID0s. The four-disk RAID0 doesn’t follow the suit.

When discussing mixed streams of requests, we supposed that the algorithms of reading from a mirrored couple use alternating requests, but we see now that this algorithm affects negatively the speed of the RAID1 and RAID10 during sequential reading. The read speed of the RAID1 array is always smaller than that of the single driver, while the RAID10 lags behind the two-disk RAID0.

The graphs of the RAID5 arrays coincide like in the DataBase pattern.

Now we enable WB caching and see what happens (in fact, caching shouldn’t bring in any changes, because we have no write requests in this pattern):

And really, none of the arrays has changed its speeds compared to the write-through mode. The only exception is the three-disk RAID5, which maximum speed is now even smaller than that of the RAID10.