Disk arrays were especially designed to group several disks into a single address space and to offer high bandwidth by exploiting data access parallelism. Understanding how this parallelism improves the performance of an array is very important to understanding the design and results presented in this paper.
A first kind of parallelism is achieved within a single request. In this case, all disks work together to fulfill a single request and thus the time spent transferring data from the magnetic surface is divided by the number of disks.
A second kind of parallelism occurs when several requests do not use all disks in the array and can be served in parallel. This kind of parallelism makes sense when requests are small compared to the size of the stripe. If requests are large, they will use all disks and the parallelism between requests will decrease significantly.
One of the most important performance problems in a RAID5 is the small-write problem. In this kind of array, writing data implies that the parity information has to be updated. For this reason, it is recommended to write full stripes as the parity can be computed only using the blocks to be written. If a write operation does not write all the blocks in a stripe, some blocks have to be read from the array to recompute the new parity. This means that a write also implies a read, which penalizes the performance of the operation.
In this work, we consider the read-write-modify approach as opposed to the regenerate-write [3] because it offers more parallelism between requests. The first one (read-write-modify) consists of reading the same blocks that are being written and the parity block. Then, the parity block is XORed with the old blocks (just read) and with the new blocks (just to be written) obtaining the new parity block. The other possibility (regenerate-write) is to read the blocks that are not being modified and thus the new parity blocks can be computed because we have all the blocks in the stripe.