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Spatial Locality

The key observation is that given the geometry and design of the modern day disks, sequential bandwidth of the disks is significantly higher (for example, more than $ 10$ times) than its performance on 100% random write workload. The goal is to exploit this differential by introducing spatial locality in the destage order.

This goal has been extensively studied in the context of disk scheduling algorithms. The key constraint in disk scheduling is to ensure fairness or avoid starvation that occurs when a disk I/O is not serviced for an unacceptably long time. In other words, the goal is to minimize the average response time and its variance. For detailed reviews on disk scheduling, see [23,24,25,26]. A number of algorithms are known: First-come-first-serve (FCFS) [27], Shortest seek time first (SSTF) [28] serves the I/O that leads to shortest seek, Shortest access time first (SATF), SCAN [28] serves I/Os first in increasing order and then in decreasing order of their logical addresses, Cyclical SCAN (CSCAN)[29] serves I/Os only in the increasing order of their logical addresses. There are many other variants known as LOOK [30], VSCAN [31], FSCAN [27], Shortest Positioning Time First (SPTF) [26], GSTF and WSTF [24], and Largest Segment per Track LST [11,32].

In the context of the present paper, we are interested in write caching at an upper level in the memory hierarchy, namely, for a storage controller. This context differs from disk scheduling in two ways. First, the goal is to maximize throughput without worrying about fairness or starvation for writes. This follows since as far as the writer is concerned, the write requests have already been completed after they are written in the NVS. Furthermore, there are no reads that are being scheduled by the algorithm. Second, in disk scheduling, detailed knowledge of the disk head and the exact position of various outstanding writes relative to this head position and disk motion is available. Such knowledge cannot be assumed in our context. For example, [21] found that applying SATF at a higher level was not possible. They concluded that ``$ ...$ we found that modern disks have too many internal control mechanisms that are too complicated to properly account for in the disk service time model. This exercise lead us to conclude that software-based SATF disk schedulers are less and less feasible as the disk technology evolves.'' Reference [21] further noted that ``Even when a reasonably accurate software-based SATF disk scheduler can be successfully built, the performance gain over a SCAN-based disk scheduler that it can realistically achieve appears to be insignificant $ ...$''. The conclusions of [21] were in the context of single disks, however, if applied to RAID-5, their conclusions will hold with even more force.

For these reasons, in this paper, we focus on CSCAN as the fundamental spatial locality algorithm that is suitable in our context. The reason that CSCAN works reasonably well is that at anytime it issues a few outstanding writes that all fall in a thin annulus on the disk, see, Figure 1. Hence, CSCAN helps reduce seek distances. The algorithm does not attempt to optimize for further rotational latency, but rather trusts the scheduling algorithm inside the disk to order the writes and to exploit this degree of freedom. In other words, CSCAN does not attempt to outsmart or outguess the disk's scheduling algorithm, but rather complements it.

Figure 1: A visual depiction of how CSCAN localizes the outstanding writes on a thin annulus on the disk platter.
\epsfig{figure=annulus.eps,width=2.5in} \end{center} \end{figure}

Figure 2: A plot of the size of NVS used by CSCAN versus the throughput (in IOPS) achieved by the algorithm on a workload that writes 4KB pages randomly over a single disk. It can be seen that throughput seems to grows logarithmically as NVS size grows. Also, as the queue size, namely, the number of outstanding requests issued by CSCAN to the disk increases, the throughput also increases.
{\small Random Write Workload \\
Single Disk with ...} \centerline{
\epsfig{figure=data/cscangood.eps,height=2.25in} } \end{figure}

In Figure 2, we demonstrate that as the size of NVS managed by CSCAN grows, so does the achieved throughput. We use a workload that writes 4KB pages randomly over a single disk, and that has nearly 100% write misses. We also use several queue sizes that control the maximum number of outstanding writes that CSCAN can issue to the disk. It appears that throughput grows proportionally to the logarithm of the NVS size. As the size of NVS grows, assuming no starvation at the underlying disk, the average thickness of the annulus in Figure 1 should shrink - thus permitting a more effective utilization of the disk. Observe that the disks continuously rotate at a constant number of revolutions per second. CSCAN attempts to increase the number of writes that can be carried out per revolution.

next up previous
Next: Combining Temporal and Spatial Up: Prior Work Previous: Temporal Locality
Binny Gill 2005-10-17